Publikationen Lehrstuhl Dette

2024

  • Bastian, P. 
    Detecting relevant deviations from the white noise assumption for non-stationary time series.
    arXiv: 2411.06909
  • Chakraborty, S., Dette, H., Kroll, M. 
    Optimal Designs for Regression on Lie Groups.
    arXiv: 2410.00429
  • Bücher, A., Dette, H. 
    On the lack of weak continuity of Chatterjee's correlation coefficient.
    arXiv: 2410.11418
  • Dörnemann, N., Dette, H. 
    Detecting Change Points of Covariance Matrices in High Dimensions.
    arXiv: 2409.15588
  • Kühnert, S.
    Estimating lagged (cross-)covariance operators of L^p-m-approximable processes in Cartesian product Hilbert spaces
    Journal of Time Series Analysis
    DOI: 10.1111/jtsa.12772
  • Kroll, M. 
    Asymptotic Normality of Chatterjee's Rank Correlation.
    arXiv: 2408.11547
  • Blümel, S., Beule, L.; Bissantz, N., Kirchner, W.H., Haberlah-Korr, V. 
    Taxon-specific response of natural enemies to different flower strip mixtures.
    Journal of Applied Ecology  
  • Kühnert, S., Rice, G. and Aue, A.,
    Estimating invertible processes in Hilbert spaces, with applications to functional ARMA processes.
    arXiv: 2407.12221 
  • Bastian, P. and Dette H.
    Gradual changes in functional time series.
    arXiv: 2407.07996 
  • Chen, H., Dette H. and Yu J.
    Multi-resolution subsampling for large-scale linear classification.
    arXiv: 2407.05691 
  • Bissantz, N.,  Dunsche, M., Nurullah, E., Maehre, M., Merget, R., Schwenk and J., Somorovsky, J.
    With Great Power Come Great Side Channels: Statistical Timing Side-Channel Analyses with Bounded Type-1 Errors.
    USENIX Security Symposium
  • Askin, Ö., Dunsche, M. and Kutta, T.
    Lower Bounds for Rényi Differential Privacy in a Black-Box Setting.
    IEEE Computer Society, Vol.: 1, Pages: 137
  • Dette, H., Tang, J.
    Simultaneous semiparametric inference for single-index models.
    arXiv: 2407.01874
  • Dette, H., Rohde, A.
    Nonparametric bootstrap of high-dimensional sample covariance matrices.
    arXiv: 2406.16849
  • Kroll, M.
    Asymptotic Normality of U-Statistics is Equivalent to Convergence in the Wasserstein Distance.
    arXiv: 2405.06477
  • Ale-Ebrahim, A, Barsl, N., Bernhard, L., Bissantz, N.,Crump, A., Holzl, T., Muench, M., Scharnowski, T.,Schiller, N., Schloegel, M. (2024).
    SoK: Prudent Evaluation Practices for Fuzzing
    2024 IEEE Symposium on Security and Privacy (SP)
  • Dette, H. and Graw, C.
    Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent.
    arXiv: 2405.12553
  • Bretz, F., Dette, H. and Koletzko, L.
    Testing for similarity of dose response in multi-regional clinical trials.
    arXiv: 2404.17682
  • Dette, H. and Tang, J.
    New energy distances for statistical inference on infinite dimensional Hilbert spaces without moment conditions.
    arXiv: 2403.11489
  • Dette, H., Eckle, T. and van Delft, A.
    Balancing the edge effect and dimension of spectral spatial statistics under irregular sampling with applications to isotropy testing.
    arXiv: 2401.07522
  • Binder, N., Dette, H. and Möllenhoff, K.
    Testing similarity of parametric competing risks models for identifying potentially similar pathways in healthcare.
    arXiv: 2401.04490

2023

  • Bastian, P., Basu, R. and Dette, H.
    Multiple change point detection in functional data with applications to biomechanical fatigue data.
    arXiv: 2312.11108
  • Dette, H. and Kroll, M.
    A Simple Bootstrap for Chatterjee's Rank Correlation.
    arXiv: 2308.01027
  • Dasgupta, S. and Dette, H.
    Efficient subsampling for exponential family models.
    arXiv: 2306.16821
  • Dörnemann, N. and Dette, H.
    A CLT for the difference of eigenvalue statistics of sample covariance matrices.
    arXiv: 2306.09050
  • Bastian, P., Dette, H. and Koletzko, L.
    Testing equivalence of multinomial distributions - a constrained bootstrap approach.
    arXiv: 2305.08609
  • Ai, M., Dette, H., Liu, Z. and Yu, J.
    A reinforced learning approach to optimal design under model uncertainty.
    arXiv: 2303.15887
  • Dette, H., Janisch, R., Kroll, M. and Schmalofski, T.
    Towards active learning: A stopping criterion for the sequential sampling of grain boundary degrees of freedom.
    arXiv: 2302.01603
  • Bastian, P., Dette, H., Koletzko, L. and Möllenhoff, K.
    Comparing regressions curves - an L1-point of view.
    arXiv: 2302.01121
  • Dette, H., Dierickx, G. and Kutta, T.
    Testing separability for continuous functional data.
    arXiv: 2301.04487

2022

  • Askin, Ö., Dunsche, M. and Kutta, T.
    Lower Bounds for Rényi Differential Privacy in a Black-Box Setting.
    arXiv: 2212.04739
  • Dette, H. and Dörnemann, N.
    Fluctuations of the diagonal entries of a large sample precision matrix.
    arXiv: 2211.00474
  • Bastian, P., Dette, H. and Heiny, J.
    Independence testing in high dimensions.
    arXiv: 2210.17439
  • Dörnemann, N. and Heiny, J.
    Limiting spectral distribution for large sample correlation matrices.
    arXiv: 2208.14948
  • van Delft, A. and Dette, H.
    A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes.
    arXiv: 2208.10158
  • Dette, H. and Kutta, T.
    Validating Approximate Slope Homogeneity in Large Panels.
    arXiv: 2205.02197
  • Binder, N., Dette, H., Franz, J., Zöller, D., Suarez-Ibarrola, R., Gratzke, Ch., Binder, H. and Miernik, A.
    Data Mining in Urology: Understanding Real-world Treatment Pathways for Lower Urinary Tract Systems via Exploration of Big Data.
    Pubmed: 35414493
  • Dörnemann, N.
    Likelihood ratio tests under model misspecification in high dimensions.
    arXiv: 2203.05423
  • Dette, H. and Quanz, P.
    Detecting relevant changes in the spatiotemporal mean function.
    arXiv: 2203.04716
  • Dette, H. and Tang, J.
    An RKHS approach for pivotal inference in functional linear regression.
    arXiv: 2202.08051
  • Strothmann, C., Dette, H. and Siburg, K. F.
    Rearranged dependence measures.
    arXiv: 2201.03329

2021

  • Goto, Y., Kley, T., Van Hecke, R., Volgushev, S., Dette, H. and Hallin, M.
    The integrated copula spectrum.
    arXiv: 2112.07077
  • Kroll, M., Schmalofski, T., Dette, H. and Janisch, R.
    Efficient prediction of grain boundary energies from atomistic simulations via sequential design.
    arXiv: 2111.13767
  • Dunsche, M., Kutta, T. and Dette, H.
    Multivariate mean comparison under differential privacy.
    arXiv: 2110.07996
  • Györfi, L. and Kroll, M.
    Multivariate density estimation from privatised data: universal concistency and minimax rates.
    arXiv: 2107.12649
  • Dette, H. and Tang, J.
    Statistical inference for function-on-function linear regression.
    arXiv: 2109.13603
  • Binder, N., Möllenhoff, K., Sigle, A. and Dette, H.
    Similarity of competing risks models with constant intensities in an application to clinical healthcare pathways involving prostate cancer surgery.
    arXiv: 2109.09830
  • Dette, H. and Wu, W.
    Confidence surfaces for the mean of locally stationary functional time series.
    arXiv: 2109.03641
  • Askin, Ö., Kutta, T. and Dette, H.
    Statistical Quantification of Differential Privacy: A Local Approach.
    arXiv: 2108.09528
  • Kutta, T., Dierickx, G. and Dette, H.
    Statistical inference for the slope parameter in functional linear regression.
    arXiv: 2108.07098
  • Dörnemann, N. and Dette, H.
    Linear spectral statistics of sequential sample covariance matrices.
    arXiv: 2107.10036
  • Dette, H. and Kroll, M.
    Asymptotic equivalence for nonparametric regression with dependent errors: Gauss-Markov processes.
    arXiv: 2104.09485
  • Solea, E. and Dette, H.
    Nonparametric and high-dimensional functional graphical models.
    arXiv: 2103.10568
  • Dette, H. and Zhigljavsky, A.
    Reproducing kernel Hilbert spaces, polynomials and the classical moment problems.
    arXiv: 2101.11968
  • Schorning, K. and Dette, H.
    Optimal designs for comparing regression curves - dependence within and between groups.
    arXiv: 2101.05654

2020

  • Loingeville, F., Bertrand, J., Nguyen, T. T., Sharan, S., Feng, K., Sun, W., Han, J., Grosser, S., Zhao, L., Fang, L., Möllenhoff, K., Dette, H. and Mentré, F.
    New model-based bioequivalence statistical approaches for pharmacokinetic studies with sparse sampling.
    Pubmed: 33125589
  • Kroll, M.
    Adaptive spectral density estimation by model selection under local differential privacy.
    arXiv: 2010.04218
  • Dette, H., Melas, V. B. and Shpilev, P.
    A note on optimal designs for estimating the slope of a polynomial regression.
    arXiv: 2009.08853
  • Bücher, A., Dette, H. and Heinrichs, F.
    A Portmanteau-type test for detecting serial correlation in locally stationary functional time series.
    arXiv: 2009.07312
  • Dette, H. and Schumann, M.
    Difference-in-differences estimation under non-parallel trends.
  • Dette, H., Golosnoy, V. and Kellermann, J.
    Correcting intraday periodicity bias in realized volatility measures.
  • Dette, H. and Kokot, K.
    Detecting relevant differences in the covariance operators of functional time series - a sup-norm approach.
    arXiv: 2006.07291
  • Gösmann, J., Stoehr, C., Heiny, J. and Dette, H.
    Sequential change point detection in high dimensional time series.
    arXiv: 2006.00636
  • Heinrichs, F. and Dette, H.
    A distribution free test for changes in the trend function of locally stationary processes.
    arXiv: 2005.11132
  • Dette, H. and Kokot, K.
    Efficient tests for bio-equivalence in functional data.
    arXiv: 2004.12364
  • van Delft, A. and Dette, H.
    Pivotal tests for relevant differences in the second order dynamics of functional time series.
    arXiv: 2004.04724
  • Dette, H., Dierickx, G. and Kutta, T.
    Quantifying deviations from separability in space-time functional processes.
    arXiv: 2003.12126
  • Dette, H., Liu, X. and Yue, R.-X.
    Design admissibility and de la Garza phenomenon in multi-factor experiments.
    arXiv: 2003.09493
  • Zhou, Z. and Dette, H.
    Statistical inference for high dimensional panel functional time series.
    arXiv: 2003.05968 (Code)
  • Bücher, A., Dette, H. and Heinrichs, F.
    Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators.
    arXiv: 2002.06143
  • Dette, H. and Wu, W.
    Prediction in locally stationary time series.
    arXiv: 2001.00419

2019

  • Kirch, C. and Stöhr, C.
    Sequential change point tests based on U-statistics.
    arXiv: 1912.08580
  • Dette, H. and Kutta, T.
    Detecting structural breaks in eigensystems of functional time series.
    arXiv: 1911.07580
  • Möllenhoff, K., Dette, H. and Bretz, F.
    Equivalence tests for binary efficacy-toxicity responses.
    arXiv: 1910.08769
  • Aue, A., Dette, H. and Rice, G.
    Two-sample tests for relevant differences in the eigenfunctions of covariance operators.
    arXiv: 1909.06098
  • Möllenhoff, K., Loingeville, F., Bertrand, J., Nguyen, T. T., Sharan, S., Sun, G., Grosser, S., Zhao, L., Fang, L., Mentré, F. and Dette, H.
    Efficient model-based bioequivalence testing.
    Pubmed: 32696053
  • Dette, H., Dhar, S. S. and Wu, W.
    Identifying shifts between two regression curves.
    arXiv: 1908.04328
  • Bodnar, T., Dette, H., Parolya, N. and Thorsén, E.
    Sampling Distributions of Optimal Portfolio Weights and Characteristics in Low and Large Dimensions.
    arXiv: 1908.04243
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Prediction in regression models with continuous observations.
    arXiv: 1908.04106
  • Gruszka, P., Stammen, C., Bissantz, N. and Jensen, M. K.
    Pain vs. comfort diary: A fully remote app-based experiment.
    Pubmed: 31233662
  • Dette, H., Melas, V. B. and Shpilev, P.
    Optimal designs for estimating individual coefficients in polynomial regression with no intercept.
    arXiv: 1906.08343
  • Gösmann, J., Kley, T. and Dette, H.
    A new approach for open-end sequential change point monitoring.
    arXiv: 1906.03225
  • van Delft, A.
    A note on quadratic forms of stationary functional time series under mild conditions.
    arXiv: 1905.13186
  • Dette, H. and Dörnemann, N.
    Likelihood ratio tests for many groups in high dimensions.
    arXiv: 1905.10354
  • Dette, H., Melas, V. B. and Shpilev, P.
    Some explicit solutions of c-optimal design problems for polynomial regression.
  • Alhorn, K., Dette, H. and Schorning, K.
    Optimal designs for model averaging in non-nested models.
    arXiv: 1904.01228
  • Stöhr, C., Aston, J. A. D. and Kirch, C.
    Detecting changes in the covariance structure of functional time series with application to fMRI data.
    arXiv: 1903.00288
  • Möllenhoff, K., Bretz, F. and Dette, H.
    Equivalence of regression curves sharing common parameters.
    arXiv: 1902.03456
  • Kutta, T., Bissantz, N., Chown, J. and Dette, H.
    The empirical process of residuals from an inverse regression.
    arXiv: 1902.03418

2018

  • Dette, H., Schorning, K. and Konstantinou, M.
    Optimal designs for series estimation in nonparametric regression with correlated data.
    arXiv: 1812.05553
  • Chown, J., Bissantz, N. and Dette, H.
    Goodness-of-fit testing the error distribution in multivariate indirect regression.
    arXiv: 1812.02409
  • Collignon, O., Möllenhoff, K. and Dette, H.
    Equivalence analyses of dissolution profiles with the Mahalanobis distance: a regulatory perspective and a comparison with a parametric maximum deviation-based approach.
    Pubmed: 30515869
  • Durastanti, C. and Patschkowski, T.
    Aliasing effects for random fields over spheres of arbitrary dimension.
    arXiv: 1811.11708
  • Dette, H., Schüler, T. and Vetter, M.
    Multiscale change point detection for dependent data.
    arXiv: 1811.05956
  • van Delft, A. and Dette, H.
    A similarity measure for second order properties of non-stationary functional time series with applications to clustering and testing. arXiv: 1810.08292
  • Dette, H., Kokot, K. and Volgushev, S.
    Testing relevant hypotheses in functional time series via self-normalization.
    arXiv: 1809.06092
  • Bücher, A., Volgushev, S. and Zou, N.
    On Second Order Conditions in the Multivariate Block Maxima and Peak over Threshold Method.
    arXiv: 1808.10828
  • Bücher, A., Dette, H. and Heinrichs, F.
    Detecting deviations from second-order stationarity in locally stationary functional time series.
    arXiv: 1808.04092
  • Dette, H., Pan, G. M. and Yang, Q.
    Estimating a change point in a sequence of very high-dimensional covariance matrices.
    arXiv:1807.10797
  • Alhorn, K., Schorning, K. and Dette, H.
    Optimal designs for frequentist model averaging.
    arXiv: 1807.05234
  • Bücher, A. and Zhou, C.
    A horse racing between the block maxima method and the peak-over-threshold approach.
    arXiv: 1807.00282
  • Dette, H., Tomecki, D. and Venker, M.
    Random Moment Problems under Constraints.
    arXiv: 1806.04652
  • Gude, P., Rieckert, C., Bissantz, N., Weber, T. P., Vogelsang, H., Dazert, S. and Thomas, J. P.
    Analgetikabedarf bei Kindern im Alter zwischen 2 und 12 Jahren nach Tonsillenoperationen / Need of analgetics in children aged 2-12 years after tonsil surgery.
    Pubmed: 29660744
  • Chown, J., Heuchenne, C. and Van Keilegom, I.
    The nonparametric location-scale mixture cure model.
    arXiv: 1803.03512
  • Bagchi, P. and Dhar, S. S.
    A study on the least square estimator of multiple isotonic regression function.
  • Hoffmann, M.
    On detecting changes in the jumps of arbitrary size of a time-continuous stochastic process.
    arXiv: 1802.08658
  • Dette, H. and Gösmann, J.
    A likelihood ratio approach to sequential change point detection for a general class of parameters.
    arXiv: 1802.07696
  • Dette, H. and Wu, W.
    Change point analysis in non-stationary processes - a mass excess approach.
    arXiv: 1801.09874
  • van Delft, A. and Eichler, M.
    A note on Herglotz's theorem for time series on function spaces.
    arXiv: 1801.04262

2017

  • Claeys, T., Neuschel, T. and Venker, M.
    Boundaries of sine kernel universality for Gaussian perturbations of Hermitian matrices.
    arXiv: 1712.08432
  • Schorning, K. and Konstantinou, M.
    Bayesian optimal designs for dose-response curves with common parameters.
    arXiv: 1711.05704
  • Dette, H., Konstantinou, M., Schorning, K. and Gösmann, J.
    Optimal designs for regression with spherical data.
    arXiv: 1710.10526
  • Bagchi, P. und Dette, H.
    A Test for Separability in Covariance Operators of Random Surfaces.
    arXiv: 1710.08388
  • Dette, H., Kokot, K. and Aue, A.
    Functional data analysis in the Banach space of continuous functions.
    arXiv: 1710.07781
  • Schorning, K., Dette, H., Kettelhake, K. and Möller, T.
    Optimal designs for enzyme inhibition kinetic models.
    arXiv: 1709.04952
  • Bücher, A., Fermanian, J.-D. and Kojadinovic, I.
    Combining cumulative sum change-point detection tests for assessing the stationarity of univariate time series.
    arXiv: 1709.02673
  • Dette, H., Tomecki, D. and Venker, M.
    Universality in Random Moment Problems.
    arXiv: 1709.02266
  • van Delft, A., Characiejus, V. and Dette, H.
    A nonparametric test for stationarity in functional time series.
    arXiv: 1708.05248
  • Bodnar, T., Dette, H. and Parolya, N.
    Testing for Independence of Large Dimensional Vectors.
    arXiv: 1708.03964
  • Tomecki, D. and Dette, H.
    Determinants of Random Block Hankel Matrices.
    arXiv: 1706.08914
  • Bücher, A. and Segers, J.
    Inference for heavy tailed stationary time series based on sliding blocks.
    arXiv: 1706.01968
  • Bücher, A. and Kojadinovic, I.
    A note on conditional versus joint unconditional weak convergence in bootstrap consistency results.
    arXiv: 1706.01031
  • Möllenhoff, K., Dette, H., Kotzagiorgis, E., Volgushev, S. and Collignon, O.
    Regulatory assessment of drug dissolutions profiles comparability via maximum deviation.
    Pubmed: 29862526
  • Bondzio, L., Scheit, M., Berghaus, B., Bissantz, N., Bakaba, J. E. and Ortlepp, J.
    Sicherung von bevorrechtigten umlaufenden Radwegen an innerörtlichen Kreisverkehren.
  • Dette, H. and Gösmann, J.
    Relevant change points in high dimensional time series.
    arXiv: 1704.04614
  • Hoffmann, M., Vetter, M. and Dette, H.
    Nonparametric inference of gradual changes in the jump behaviour of time-continuous processes.
    arXiv: 1704.04040
  • Dunker, F., Eckle, K., Proksch, K. and Schmidt-Hieber, J.
    Tests for qualitative features in the random coefficients model.
    arXiv: 1704.01066
  • Van Hecke, R., Volgushev, S. and Dette, H.
    Fourier analysis of serial dependence measures.
    arXiv: 1703.04320
  • Lucka, F., Proksch, K., Brune, C., Bissantz, N., Burger, M., Dette, H. and Wübbeling, F.
    Risk Estimators for Choosing Regularization Parameters in Ill-Posed Problems - Properties and Limitations.
    arXiv: 1701.04970
  • Aue, A. and van Delft, A.
    Testing for stationarity of functional time series in the frequency domain.
    arXiv: 1701.01741

2016

  • Bagchi, P., Characiejus, V. and Dette, H.
    A simple test for white noise in functional time.
    arXiv: 1612.04996
  • Akashi, F., Dette, H. and Liu, Y.
    Change point detection in autoregressive models with no moment assumptions.
    arXiv: 1612.01520
  • Dette, H., Guchenko, R., Melas, V. B. and Wong, W. K.
    Optimal discrimination designs for semi-parametric models.
    arXiv: 1612.00328
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Best linear unbiased estimators in continuous time regression models.
    arXiv: 1611.09804
  • Birr, S., Dette, H., Hallin, M., Kley, T. and Volgushev, S.
    On Wigner-Ville Spectra and the Unicity of Time-Varying Quantile-Based Spectral Densities.
    arXiv: 1611.07253
  • Eckle, K., Bissantz, N. and Dette, H.
    Multiscale inference for multivariate deconvolution.
    arXiv: 1611.05201
  • Chown, J. and Müller, U. U.
    Detecting heteroskedasticity in nonparametric regression using weighted empirical processes.
    arXiv: 1610.09139
  • Chown, J.
    Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data.
    arXiv: 1610.08768
  • Bissantz, N., Chown, J. and Dette, H.
    Regularization parameter selection in indirect regression by residual based bootstrap.
    arXiv: 1610.08663
  • Dette, H., Golosnoy, V. and Kellermann, J.
    The effect of intraday periodicity on realized volatility measures.
  • Michalak, J., Probst, T., Heidenreich, T., Bissantz, N. and Schramm, E.
    Mindfulness-Based Cognitive Therapy and a Group Version of the Cognitive Behavioral Analysis System of Psychotherapy for Chronic Depression: Follow-Up Data of a Randomized Controlled Trial and the Moderating Role of Childhood Adversities.
    Pubmed: 27744451
  • Birke, M., Neumeyer, N. and Volgushev, S.
    The independence process in conditional quantile location-scale models and an application to testing for monotonicity.
    arXiv: 1609.07696
  • Berghaus, B. and Bücher, A.
    Weak convergence of a pseudo maximum likelihood estimator for the extremal index.
    arXiv: 1608.01903
  • Dette, H., Goesmann, J., Greiff, C. and Janisch, R.
    Efficient sampling in materials simulation - exploring the parameter space of grain boundaries.
  • Bretz, F., Möllenhoff, K., Dette, H., Liu, W. and Trampisch, M.
    Assessing the similarity of dose response and target doses in two non-overlapping subgroups.
    arXiv: 1607.05424
  • Roslyakova, I., Sundman, B., Dette, H., Zhang, L. and Steinbach, I.
    Modeling of Gibbs energies of pure elements down to 0K using segmented regression.
  • Duarte, B. P. M., Wong, W. K. and Dette, H.
    Adaptive grid semidefinite programming for finding optimal designs.
  • Konstantinou, M. and Dette, H.
    Bayesian D-optimal designs for error-in-variables models.
    arXiv: 1605.04055
  • Krämer, W. and Dette, H.
    Beyond inequality: A novel measure of skewness and its properties.
  • Dette, H., Ley, C. and Rubio, F. J.
    Natural (non-)informative priors for skew-symmetric distributions.
    arXiv: 1605.02880
  • Eckle, K., Bissantz, N., Dette, H., Proksch, K. and Einecke, S.
    Multiscale inference for a multivariate density with applications to X-ray astronomy.
    arXiv: 1604.04405
  • Feller, C., Schorning, K., Dette, H., Bermann, G. and Bornkamp, B.
    Optimal designs for dose response curves with common parameters.
    arXiv: 1603.04500
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Optimal designs for regression models with autoregressive errors structure.
    arXiv: 1602.03794
  • Dette, H., Schorning, K. and Konstantinou, M.
    Optimal designs for comparing regression models with correlated observations.
    arXiv: 1601.06722
  • Bücher, A. and Segers, J.
    On the maximum likelihood estimator for the Generalized Extreme-Value distribution.
    arXiv: 1601.05702
  • Dette, H., Kettelhake, K. Schorning, K., Wong, W. K. and Bretz, F.
    Optimal designs for active controlled dose finding trials with efficacy-toxicity outcomes.
    arXiv: 1601.00797

2015

  • Dette, H., Melas, V. B. and Shpilev, P.
    T-optimal discriminating designs for Fourier regression models.
    arXiv: 1512.07441
  • Dunker, F.
    Convergence of the risk for nonparametric IV quantile regression and nonparametric IV regression with full independence.
    PDF
  • Bücher, A. and Segers, J.
    Maximum likelihood estimation for the Fréchet distribution based on block maxima extracted from a time series.
    arXiv: 1511.07613
  • Dette, H., Konstantinou, M. and Zhigljavsky, A.
    A new approach to optimal designs for correlated observations.
    arXiv: 1511.01881
  • Bodnar, T., Dette, H. and Parolya, N.
    Spectral analysis of the Moore-Penrose inverse of a large dimensional sample covariance matrix.
    arXiv: 1509.06121
  • Dette, H., and Tomecki, D.
    Hankel determinants of random moment sequences.
    arXiv: 1508.00617
  • Schorning, K., Bornkamp, B., Bretz, F. and Dette, H.
    Model Selection versus Model Averaging in Dose Finding Studies.
    arXiv: 1508.00281
  • Dette, H., Guchenko, R. and Melas, V. B.
    Efficient computation of Bayesian optimal discriminating designs.
    arXiv: 1508.00279
  • Schmitt, T. A., Schäfer, R., Dette, H. and Guhr, T.
    Quantile Correlations: Uncovering temporal dependencies in financial time series.
    arXiv: 1507.04990
  • Hoffmann, M. and Vetter, M.
    Weak convergence of the empirical truncated distribution function of the Lévy measure of an Ito semimartingale.
    arXiv: 1506.07404
  • Bissantz, K., Bissantz, N. and Proksch, K.
    Monitoring of significant changes over time in fluorescence microscopy imaging of living cells.
  • Dette, H., Möllenhoff, K., Volgushev, S. and Bretz, F.
    Equivalence of dose response curves.
    arXiv: 1505.05266
  • Bücher, A., Kinsvater, P. and Kojadinovic, I.
    Detecting breaks in the dependence of multivariate extreme-value distributions.
    arXiv: 1505.00954
  • Dette, H., Wu, W. and Zhou, Z.
    Change point analysis of second order characteristics in non-stationary time series.
    arXiv: 1503.08610
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Optimal designs in regression with correlated errors.
    arXiv: 1501.01774

2014

  • Bücher, A. and Kojadinovic, I.
    Dependent multiplier bootstraps for non-degenerate U-statistics under mixing conditions with applications.
    arXiv: 1412.5875
  • Bücher, A., Hoffmann, M., Vetter, M. and Dette, H.
    Nonparametric tests for detecting breaks in the jump behaviour of a time-continuous process.
    arXiv: 1412.5376
  • Dette, H., Melas, V. B. and Guchenko, R.
    Bayesian T-optimal discriminating designs.
    arXiv: 1412.2548
  • Bücher, A. and Kojadinovic, I.
    An overview of nonparametric tests of extreme-value dependence and of some related statistical procedures.
    arXiv: 1410.6784
  • Berghaus, B., Bücher, A. and Volgushev, S.
    Weak convergence of the empirical copula process with respect to weighted metrics.
    arXiv: 1411.5888
  • Dette, H., Kettelhake, K. and Bretz, F.
    Designing dose finding studies with an active control for exponential families.
    arXiv: 1410.8688
  • Dette, H. and Schorning, K.
    Optimal designs for comparing curves.
    arXiv: 1410.7616
  • Konstantinou, M. and Dette, H.
    Locally optimal designs for errors-in-variables models.
  • Kley, T.
    Quantile-Based Spectral Analysis in an Object-Oriented Framework and a Reference Implementation in R: The quantspec Package.
    arXiv: 1408.6755
  • Chao, S.-K., Proksch, K., Dette, H. and Härdle, W.
    Confidence Corridors for Multivariate Generalized Quantile Regression.
    arXiv: 1406.4421
  • Berghaus, B. and Bücher, A.
    Goodness-of-fit tests for multivariate copula-based time series models.
  • Skowronek, S., Volgushev, S., Kley, T., Dette, H. and Hallin, M.
    Quantile Spectral Analysis for Locally Stationary Time Series.
    arXiv: 1404.4605
  • Dette, H. and Wied, D.
    Detecting relevant changes in time series models.
    arXiv: 1403.8120
  • Dette, H., Van Hecke, R. and Volgushev, S.
    Some comments on copula-based regression.
    PDF
  • Dette, H. and Grigoriev, Y.
    E-optimal designs for second-order response surface models.
    arXiv: 1403.3805
  • Konstantinou, M., Biedermann, S. and Kimber, A.
    Optimal designs for two-parameter nonlinear models with application to survival models.
    PDF
  • Kley, T., Volgushev, S., Dette, H. and Hallin, M.
    Quantile spectral processes: Asymptotic analysis and inference.
    arXiv: 1401.8104
  • Bücher, A., El Ghouch, A. and Van Keilegom, I.
    Single-index quantile regression models for censored data.
    PDF

2013

  • Preuß, P., Sen, K. and Dette, H.
    Detecting long-range dependence in non-stationary time series.
    arXiv: 1312.7452
  • Preuß, P., Vetter, M. and Dette, H.
    A test for stationarity based on empirical processes.
    arXiv: 1312.5448
  • Dette, H., Hoyden, L., Kuhnt, S. and Schorning, K.
    Optimal designs for multi-response generalized linear models with applications in thermal spraying.
    arXiv: 1312.4472
  • Proksch, K.
    On confidence bands for multivariate nonparametric regression.
    PDF
  • Paparoditis, E. and Preuss, P.
    Estimation of the bispectrum for locally stationary processes.
  • Puchstein, R. and Preuss, P.
    Testing for stationarity in multivariate locally stationary processes.
    arXiv: 1312.1509
  • Bissantz, N., Holzmann, H. and Proksch, K.
    Confidence regions for images observed under the Radon transform.
  • Bücher, A. and Segers, J.
    Extreme value copula estimation based on block maxima of a multivariate stationary time series.
    arXiv: 1311.3060
  • Burghaus, I. and Dette, H.
    Optimal designs for nonlinear regression models with respect to non-informative priors.
    arXiv: 1311.0835
  • Bissatz, N., Dette, H. and Hildebrandt, T.
    Smooth backfitting in additive inverse regression.
    arXiv: 1311.0834
  • Vogt, M. and Dette, H.
    Detecting gradual changes in locally stationary processes.
    arXiv: 1310.4678
  • Dette, H., Melas, V. B. and Shpilev, P.
    Robust T-optimal discriminating designs.
    arXiv: 1309.4652
  • Preuß, P., Puchstein, R. and Dette, H.
    Detection of multiple structural breaks in multivariate time series.
    arXiv: 1309.1309
  • Bücher, A., Jäschke, S. and Wied, D.
    Nonparametric tests for constant tail dependence with an application to energy and finance.
  • Dette, H. and Schorning, K.
    Complete classes of designs for nonlinear regression models and principal representations of moment spaces.
    arXiv: 1306.4872
  • Bücher, A. and Kojadinovic, I.
    A dependent multiplier bootstrap for the sequential empirical copula process under strong mixing.
    arXiv: 1306.3930
  • Braess, D. and Dette, H.
    Optimal discriminating designs for several competing regression models.
    arXiv: 1306.1320
  • Bücher, A., Segers, J. and Volgushev, S.
    When uniform weak convergence fails: Empirical processes for dependence functions via epi- and hypographs.
    arXiv: 1305.6408
  • Huang, Y., Volgushev, S. and Shao, X.
    On self-normalization for censored dependent data.
    PDF
  • Volgushev, S. and Shao, X.
    A general approach to the joint asymptotic analysis of statistics from sub-samples.
    arXiv: 1305.5618
  • Bibinger, M. and Vetter, M.
    Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps.
    arXiv: 1305.3068
  • Bücher, A.
    A note on weak convergence of the sequential multivariate empirical process under strong mixing.
    arXiv: 1304.5113
  • Vetter, M.
    Inference on the Lévy measure in case of noisy observations.
    PDF
  • Paparoditis, E. and Preuß, P.
    On local properties of frequency domain based tests for stationarity.
  • Hildebrandt, T., Bissantz, N. and Dette, H.
    Additive inverse regression models with convolution-type operators.
    arXiv: 1303.4179
  • Sen, K., Preuß, P. and Dette, H.
    Measuring stationarity in long-memory processes.
    arXiv: 1303.3482
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Optimal design for linear models with correlated observations.
    arXiv: 1303.2863
  • Berghaus, B. and Bücher, A.
    Nonparametric tests for tail monotonicity.
  • Volgushev, S.
    Smoothed quantile regression processes for binary response models.
    arXiv: 1302.5644
  • Gu, J., Koenker, R. and Volgushev, S.
    Testing for Homogeneity in Mixture Models.
    arXiv: 1302.1805

2012

  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Design for regression models with correlated errors.
  • Vetter, M. and Dette, H.
    Model checks for the volatility under microstructure noise.
    arXiv: 1211.5507
  • Gralla, R., Kraft, K. and Volgushev, S.
    The effects of works councils on overtime hours - a censored quantile regression approach.
  • Preuß, P. and Vetter, M.
    Discriminating between long-range dependence and non-stationarity.
  • Dette, H., Titoff, S., Volgushev, S. and Bretz, F.
    Model identification for dose response signal detection.
  • Volgushev, S., Wagener, J. and Dette, H.
    Censored quantile regression processes under dependence and penalization.
    arXiv: 1208.5467
  • Berghaus, B., Bücher, A. and Dette, H.
    Minimum distance estimation of Pickands dependence function for multivariate distributions.
  • Preuß, P. and Hildebrandt, T.
    Comparing spectral densities of stationary time series with unequal sample sizes.
    arXiv: 1207.5659
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    'Nearly' universally optimal designs for models with correlated observations.
  • Bücher, A.
    A note on nonparametric estimation of bivariate tail dependence.
  • Vetter, M.
    Estimation of integrated volatility of volatility with applications to goodness-of-fit testing.
    arXiv: 1206.5761
  • Volgushev, S., Birke, M., Dette, H. and Neumeyer, N.
    Significance testing in quantile regression.
    arXiv: 1206.3125
  • Proksch, K., Bissantz, N. and Dette, H.
    Confidence bands for multivariate and time dependent inverse regression models.
    arXiv: 1206.2743
  • Bücher, A., Kojadinovic, I., Rohmer, T. and Segers, J.
    Detecting changes in cross-sectional dependence in multivariate time series.
    arXiv: 1206.2557
  • Bücher, A. and Ruppert, M.
    Consistent testing for a constant copula under strong mixing based on the tapered block multiplier technique.
    arXiv: 1206.1675
  • Dette, H. and Müller, W. G.
    Optimal designs for regression models with a constant coefficient of variation.
  • Dette, H., Melas, V. B. and Shpilev, P.
    T-optimal designs for discrimination between two polynomial models.
    arXiv: 1205.6283
  • Dette, H., Pepelyshev, A. and Wong, W. K.
    Optimal designs for composed models in pharmacokinetic-pharmacodynamic experiments.
    Pubmed: 22614634
  • Bücher, A. and Vetter, M.
    Nonparametric inference on Lévy measures and copulas.
    arXiv: 1205.0417
  • Dette, H., Guhlich, M. and Nagel, J.
    Distributions on matrix moment spaces.
  • Behl, P., Claeskens, G. and Dette, H.
    Focused model selection in quantile regression.
  • Wagener, J., Volgushev, S. and Dette, H.
    The quantile process under random censoring.
  • Dette, H. and Kiss, C.
    Optimal designs for rational regression models.
  • Dette, H. and Kunert, J.
    Optimal designs for the Michaelis Menten model with correlated observations.

2011

  • Dette, H., Guhlich, M. and Neumeyer, N.
    Testing for additivity in nonparametric quantile regression.
    PDF
  • Christensen, K., Podolskij, M. and Vetter, M.
    On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes.
  • Dette, H., Hallin, M., Kley, T. and Volgushev, S.
    Of copulas, quantiles, ranks and spectra: An L1-approach to spectral analysis.
    arXiv: 1111.7205
  • Bücher, A. and Volgushev, S.
    Empirical and sequential empirical copula processes under serial dependence.
    arXiv: 1111.2778
  • Bücher, A., Dette, H. and Volgushev, S.
    A test for Archimedeanity in bivariate copula models.
    arXiv: 1109.6501
  • Dette, H., Kiss, C., Benda, N. and Bretz, F.
    Optimal designs for dose finding studies with an active control.
  • Delvaux, S. and Dette, H.
    Zeros and ratio asymptotics for matrix orthogonal polynomials.
    arXiv: 1108.5155
  • Holland-Letz, T., Dette, H. and Renard, D.
    Efficient algorithms for optimal designs with correlated observations in pharmacokinetics and dose-finding studies .
    Pubmed: 21838804
  • Dette, H. and Trampisch, M.
    Optimal designs for quantile regression models.
  • Wied, D., Arnold, M., Bissantz, N. and Ziggel, D.
    A new fluctuation test for constant variances with applications to finance.
    PDF
  • Bornkamp, B., Bretz, F., Dette, H. and Pinheiro, J.
    Response-adaptive dose-finding under model uncertainty.
    arXiv: 1107.5883
  • Behl, P., Dette, H., Frondel, M. and Tauchmann, H.
    Being focused: When the purpose of inference matters for model selection.
  • Dette, H. and Melas, V. B.
    A note on the de la Garza phenomenon for locally optimal designs.
    arXiv: 1105.3575
  • Wagener, J. and Dette, H.
    The adaptive Lasso in high dimensional sparse heteroscedastic models.
  • Dette, H., Pepelyshev, A., Wong, W. K.
    Optimal experimental design strategies for detecting hormesis.
    Pubmed: 21545627
  • Birke, M. and Bissantz, N.
    Testing for symmetries in multivariate inverse problems.
  • Wagener, J. and Dette, H.
    Bridge estimators and the adaptive Lasso under heteroscedasticity.
  • Bissantz, N. and Holzmann, H.
    Asymptotics for spectral regularization estimators in statistical inverse problems.
  • Bissantz, N., Jenke, A. C., Trampisch, M., Klaassen-Mielke, R., Bissantz, K. and Holland-Letz, T.
    Hospital-based, prospective, multicentre surveillance to determine the incidence of intussusception in children aged below 15 years in Germany.
    Pubmed: 21435207
  • Preuß, P., Vetter, M. and Dette, H.
    Testing semiparametric hypotheses in locally stationary processes.
  • Dette, H., Wagener, J. and Volgushev, S.
    Nonparametric comparison of quantile curves: A stochastic process approach.
  • Dette, H., Hoderlein, S. and Neumeyer, N.
    Testing multivariate economic restrictions using quantiles: The example of Slutsky negative semidefinitenes.
  • Bissantz, N., Holzmann, H. and Pawlak, M.
    Improving PSF calibration in confocal microscopic imaging - estimating and exploiting bilateral symmetry.
    arXiv: 1102.0630
  • Bücher, A., Dette, H. and Volgushev, S.
    New estimators of the Pickands dependence function and a test for extreme-value dependence.
    arXiv: 1102.0405
  • Bücher, A. and Dette, H.
    Multiplier bootstrap of tail copulas with applications.
    arXiv: 1102.0110

2010

  • Detloff, K. C., Zander, C. D., Bissantz, N. and Ziggel, D.
    Saisonale Variation im Nahrungsverhalten des fakultativen Putzerfisches Symphodus melanocercus (Risso) im Tyrrhenischen Meer (Italien).
  • Dette, H. and Sen, K.
    Goodness-of-fit tests in long-range dependent processes under fixed alternatives.
  • Bissantz, K., Bissantz, N. and Ziggel, D.
    Diversification effects between stock indices.
    PDF
  • Dette, H., Pepelyshev, A. and Holland-Letz, T.
    Optimal designs for random effect models with correlated errors with applications in population pharmacokinetics.
    arXiv: 1011.3333
  • Dette, H., Marchlewski, M. and Wagener, J.
    Testing for a constant coefficient of variation in nonparametric regression.
  • Gamboa, F., Nagel, J., Rouault, A. and Wagener, J.
    Large Deviations for Random Matricial Moment Problems.
    arXiv: 1011.0299
  • Behl, P., Dette, H., Frondel, M. and Tauchmann, H.
    Choice is suffering: A focused information criterion for model selection.
  • Arnold, M., Bissantz, N., Wied, D. and Ziggel, D.
    A new online-test for changes in correlations between assets.
  • Dette, H., Bornkamp, B. and Bretz, F.
    On the efficiency of adaptive designs.
  • Jacod, J., Podolskij, M. and Vetter, M.
    Limit theorems for moving averages of discretized processes plus noise.
    arXiv: 1010.0335
  • Biedermann, S., Bissantz, N., Dette, H. and Jones, E.
    Optimal designs for indirect regression.
  • Dette, H., Preuß, P. and Vetter, M.
    A measure of stationarity in locally stationary processes with applications to testing.
  • Vetter, M.
    Estimation of correlation for continuous semimartingales.
  • Volgushev, S. and Dette, H.
    Nonparametric quantile regression for twice censored data.
    arXiv: 1007.3376
  • Nagel, J. and Dette, H.
    Distributions on unbounded moment spaces and random moment sequences.
    arXiv: 1007.3369
  • Bissantz, N., Steinorth, V. and Ziggel, D.
    Stabilität von Diversifikationseffekten im Markowitz-Modell.
  • Behl, P., Dette, H. and Vetter, M.
    A note on martingale transforms for model checks.
  • Dette, H., Kinsvater, T. and Vetter, M.
    Testing nonparametric hypotheses for stationary processes by estimating minimal distances.
  • Dette, H. and Hildebrandt, T.
    A note on testing hypotheses for stationary processes in the frequency domain.
  • Biedermann, S., Dette, H. and Woods, D. C.
    Optimal design for additive partially nonlinear models.
  • Birke, M. and Neumeyer, N.
    Testing monotonicity of regression functions - an empirical process approach.
  • Balabdaoui, F., Bissantz, K., Bissantz, N. and Holzmann, H.
    Demonstrating single- and multiple currents through the E. coli-SecYEG-pore: Testing for the number of modes of noisy observations.
  • Marek, C., Bissantz, N., Curio, E., Siegert, A., Tacud, B. and Ziggel, D.
    Spatial orientation of the Philippine bent-toed gecko (Cyrtodactylus philippinicus) in relation to its home range.
  • Dette, H., Siburg, K. F. and Stoimenov, P. A.
    A copula-based nonparametric measure of regression dependence.
  • Dette, H., Leonenko, N., Pepelyshev, A. and Zhigljavsky, A.
    Asymptotic optimal designs under long-range dependence error structure.
    arXiv: 1001.1817
  • Dette, H. and Pepelyshev, A.
    NPUA: A new approach for the analysis of computer experiments.

2009

  • Bücher, A. and Dette, H.
    A note on bootstrap approximations for the empirical copula process.
  • Dette, H. and Holland-Letz, T.
    A geometric characterization of c-optimal designs for heteroscedastic regression.
    arXiv: 0911.3801
  • Dette, H. and Trampisch, M.
    A general approach to D-optimal designs for weighted univariate polynomial regression models.
  • Bissantz, N., Dette, H. and Proksch, K.
    Model checks in inverse regression models with convolution-type operators.
  • Dette, H. and Heuchenne, C.
    Scale checks in censored regression.
  • Podolskij, M. and Vetter, M.
    Understanding limit theorems for semimartingales: a short survey.
  • Bücher, A., Dette, H. and Wieczorek, G.
    Testing model assumptions in functional regression models.
  • Guhlich, M., Nagel, J. and Dette, H.
    Random block matrices generalizing the classical ensembles.
    PDF
  • Biedermann, S., Dette, H. and Woods, D. C.
    Optimal designs for multivariable spline models.
  • Dette, H. and Pepelyshev, A.
    Generalized latin hypercube design for computer experiments.
  • Dette, H., Melas, V. B. and Shpilev, P.
    Optimal designs for estimating the slope in nonlinear regression.
  • Dette, H. and Titoff, S.
    Optimal discrimination designs.
    arXiv: 0908.1912
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    A new approach to optimal designs for models with correlated observations.
  • Holland-Letz, T., Dette, H. and Pepelyshev, A.
    A geometric characterization of c-optimal designs for regression models with correlated observations.
  • Dette, H., Wagener, J. and Volgushev, S.
    Nonparametric analysis of covariance using quantile curves.
  • Dette, H. Kiss, C., Bevanda, M. and Bretz, F.
    Optimal designs for the EMAX, log-linear and exponential model.
  • Dette, H., Pepelyshev, A., Shpilev, P., Wong, W. K.
    Optimal designs for estimating critical effective dose under model uncertainty in a dose response study.
  • Birke, M., Dette, H. and Stahljans, K.
    Testing symmetry of a nonparametric bivariate regression function.
  • Dette, H. and Marchlewski, M.
    A robust test for homoscedasticity in nonparametric regression.
  • Dette, H., Pepelyshev, A., Shpilev, P. and Wong, W. K.
    Optimal designs for discriminating dose response models in toxicology studies.
  • Bücher, A. and Dette, H.
    Some comments on goodness-of-fit tests for the parametric form of the copula based on L2-distances.
  • Dette, H., Melas, V. B. and Shpilev, P.
    Optimal designs for trigonometric regression models.
  • Vetter, M.
    Limit theorems for bipower variation of semimartingales.
    PDF
  • Dette, H. and Nagel, J.
    Some asymptotic properties of the spectrum of the Jacobi ensemble.
    arXiv: 0904.4091
  • Dette, H. and Wagener, J.
    Matrix measures on the unit circle, moment spaces, orthogonal polynomials and the Geronimus relations.
    arXiv: 0904.4089
  • Dette, H. and Nagel, J.
    Matrix measures, random moments and Gaussian ensembles.
    arXiv: 0904.3847
  • Anders, P., Baumgardt, H., Bissantz, N. and Portegies Zwart, S.
    How well do STARLAB and NBODY4 compare? I: Simple models.
    arXiv: 0902.4636
  • Dette, H., Pepelyshev, A. and Wong, W. K.
    Optimal designs for dose-finding experiments in toxicity studies.
    arXiv: 0902.1426
  • Dette, H., Kiss, C. and Wong, W. K.
    Robustness of optimal designs for the Michaelis-Menten model under a variation of criteria.
  • Bretz, F., Dette, H. and Pinheiro, J.
    Practical considerations for optimal designs in clinical dose finding studies.

2008

  • Bissantz, N., Dümbgen, L., Munk, A. and Stratmann, B.
    Convergence analysis of generalized iteratively reweighted least squares algorithms on convex function spaces.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Optimal designs for estimating the slope of a regression.
  • Birke, M. and Dette, H.
    A note on random orthogonal polynomials on a compact interval.
    arXiv: 0809.4936
  • Dette, H. and Hetzler, B.
    A martingale-transform goodness-of-fit test for the form of the conditional variance.
    arXiv: 0809.4914
  • Dette, H. and Reuther, B.
    Random block matrices and matrix orthogonal polynomials.
    arXiv: 0809.4601
  • Dette, H. and Paparoditis, E.
    Bootstrapping frequency domain tests in multivariate time series with an application to comparing spectral densities.
  • Dette, H. and Melas, V. B.
    A note on all-bias designs with applications in spline regression models.
  • Bissantz, N. and Birke, M.
    Asymptotic normality and confidence intervals for inverse regression models with convolution-type operators.
  • Bissantz, N., Holzmann, H. and Pawlak, M.
    Testing for image symmetries - with application to confocal microscopy.
  • Birke, M., Bissantz, N. and Holzmann, H.
    Confidence bands for inverse regression models - with application to gel electrophoresis.
  • Weißbach, R. and Dette, H.
    Bias in nearest-neighbor hazard estimation.
  • Podolskij, M. and Vetter, M.
    Bipower-type estimation in a noisy diffusion setting.
  • Birke, M.
    Shape constrained kernel density estimation.
  • Dette, H. and Scheder, R.
    A finite sample comparison of nonparametric estimates of the effective dose in quantal bioassay.
  • Dette, H. and Reuther, B.
    Some comments on quasi-birth-and death processes and matrix measures.
  • Bissantz, N., Mair, B. and Munk, A.
    A statistical stopping rule for MLEM reconstructions in PET.
    PDF
  • Bissantz, N., Claeskens, G., Holzmann, H. and Munk, A.
    Testing for lack of fit in inverse regression - with applications to biophotonic imaging.
    PDF
  • Dette, H., Melas, V. B. and Shpilev, P.
    Optimal designs for estimating pairs of coefficients in Fourier regression models.

2007

  • Pohl, M., Englmaier, P. and Bissantz, N.
    3D Distribution of Molecular Gas in the Barred Milky Way.
    arXiv: 0712.4264
  • Jacod, J., Li, Y., Mykland, P., Podolskij, M. and Vetter, M.
    Microstructure Noise in the Continuous Case: The Pre-Averaging Approach.
  • Bissantz, N. and Holzmann, H.
    Statistical Inference for Inverse Problems.
  • Dette, H. and Kiss, C.
    Optimal experimental designs for inverse quadratic regression models.
  • Dette, H. and Wieczorek, G.
    Testing for a constant coefficient of variation in nonparametric regression.
  • Bissantz, N., Mair, B. and Munk, A.
    Stochastic multi-scale selection of the stopping index in PET. Proceedings in Applied Mathematics and Mechanics.
  • Birke, M. and Bissantz, N.
    Shape constrained estimators in inverse regression models with convolution-type operator.
  • Dette, H., Pardo-Fernandéz, J. C. and van Keilegom, I.
    Goodness-of-fit Tests for Multiplicative Models with Dependent Data.
  • Dette, H. and Wiens, D. P.
    Robust Designs for Series Estimation.
  • Birke, M. and Pilz, K. F.
    Nonparametric Option Pricing with No-Arbitrage Constraints.
  • Dette, H. and Scheder, R.
    Non-crossing Marginal Effects in Additive Quantile Regression.
    PDF
  • Dette, H., Pepelyshev, A. and Zhigljavsky, A.
    Improving updating rules in multiplicative algorithms for computing D-optimal designs.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Optimal designs for smoothing splines.
  • Dette, H. and Marchlewski, M.
    A test for the parametric form of the variance function in a partial linear regression model.
  • Dette, H., Trampisch, M. and Hothorn, L. A.
    Robust Designs in Non-Inferiority Three Arm Clinical Trials with Presence of Heteroscedasticity.

    MatLab-Programm zur Berechnung der Designs
  • Podolskij, M. and Ziggel, D.
    A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models.
    PDF
  • Podolskij, M. and Ziggel, D.
    Bootstrapping Bipower Variation, Technical report.
    PDF
  • Miller, F., Guilbaud, O. and Dette, H.
    Optimal designs for estimating the interesting part of a dose-effect curve.
    Pubmed: 18027219
  • Dette, H. and Volgushev, S.
    Non-crossing nonparametric estimates of quantile curves.
  • Kinnebrock, S. and Podolskij, M.
    A Note on the Central Limit Theorem for Bipower Variation of General Functions.
    PDF
  • Dette, H. and Wiens, D. P.
    Robust designs for 3D shape analysis with spherical harmonic descriptors.
  • Anders, P., Bissantz, N., Boysen, L., de Grijs, R., Fritze - v. Alvensleben, U.
    The Young Star Cluster System in the Antennae: Evidence for a Turnover in the luminosity function.
    arXiv: astro-ph/0702413
  • Bissantz, N., Dümbgen, L., Holzmann, H. and Munk, A.
    Nonparametric confidence bands in deconvolution density estimation.
    PDF
  • Bretz, F., Dette, H., Pepelyshev, A. and Pinheiro, J.
    Optimal designs for dose finding studies.

2006

  • Birke, M.
    Central limit theorems for the integrated squared error of derivative estimators.
  • Birke, M. and Dette, H.
    Testing strict monotonicity in nonparametric regression.
  • Podolskij, M. and Vetter, M.
    Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Optimal designs for free knot least squares splines.
  • Christensen, K., Podolskij, M. and Vetter, M.
    Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise.
  • Christensen, K. and Podolskij, M.
    Range-Based Estimation of Quadratic Variation.
  • Strigul, N., Dette, H. and Melas, V. B.
    A practical guide for optimal designs of experiments in the Monod model.
  • Dette, H. and Weißbach, R
    A Bootstrap Test for the Comparison of Nonlinear Time Series - with Application to Interest Rate Modelling.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Optimal designs for statistical analysis with Zernike polynomials.
  • Biedermann, S., Dette, H. and Hoffmann, P.
    Constrained optimal discriminating designs for Fourier regression models.
  • Dette, H. and Ziggel, D.
    Discount curve estimation by monotonizing McCulloch Splines.
  • Dette, H. and Hetzler, B.
    A simple test for the parametric form of the variance function in nonparametric regression.
  • Biedermann, S., Nagel, E.-R., Munk, A., Holzmann, H. and Steland, A.
    Tests in a Case-Control Design Including Relatives.
    PDF
  • Dette, H., Kunert, J. and Pepelyshev, A.
    Exact optimal designs for weighted least squares analysis with correlated errors.

2005

  • Dette, H. and Podolskij, M.
    Testing the parametric form of the volatility in continuous time diffusion models - an empirical process approach.
  • Dette, H. and Weißbach, R.
    Kolmogorov-Smirnov-type testing for the partial homogeneity of Markov processes - with application to credit risk.
  • Kiwitt, S., Nagel, E.-R. and Neumeyer, N.
    Empirical likelihood estimators for the error distribution in nonparametric regression models.
  • Neumeyer, N.
    A note on uniform consistency of monotone function estimators.
    PS
  • Dette, H. and van Keilegom, I.
    A new test for the parametric form of the variance function in nonparametric regression.
  • Hall, P. and Neumeyer, N.
    Estimating a bivariate density when there are extra data on one or both components.
  • Birke, M. and Dette, H.
    A note on estimating a smooth monotone regression by combining kernel and density estimates.
  • Dette, H., Reuther, B., Studden, W. J. and Zygmunt, M.
    Matrix measures and random walks.
  • Biedermann, S., Dette, H. and Pepelyshev, A.
    Optimal Discrimination Designs for Exponential Regression Models.
  • Dette, H. and Melas, V. B.
    A note on some extremal problems for trigonometric polynomials.
  • Birke, M. and Dette, H.
    Estimating a convex function in nonparametric regression.
  • Dette, H., Melas, V. B., Pepelyshev, A. and Strigul, N.
    Robust and efficient design of experiments for the Monod model.
    Pubmed: 15808874
  • Christensen, K. and Podolski, M.
    Asymptotic Theory for Range-Based Estimation of integrated Variance of a Continuous Semi-Martingale.
  • Dette, H. and Scheder, R.
    Strictly monotone and smooth nonparametric regression for two or more variables.
  • Dette, H., Melas, V. B. and Shpilev, P.
    Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models.
    PDF
  • Dette, H. and Pepelyshev, A.
    Efficient experimental designs for sigmoidal growth models.
  • Biedermann, S., Dette, H. and Zhu, W.
    Geometric construction of optimal designs for dose-response models with two parameters.
  • Dette, H. and Gamboa, F.
    Asymptotic properties of the algebraic moment range process.
  • Mora, J. and Neumeyer, N.
    The two-Sample Problem with Regression Errors: An Empirical Process Approach.
  • Biedermann, S., Dette, H. and Zhu, W.
    Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals.

2004

  • Braess, D. and Dette, H.
    On the number of support points of maximin and Bayesian D-optimal designs in nonlinear regression models.
    PS
  • Dette, H. and Imhof, L. A.
    Uniform approximation of eigenvalues in Laguerre and Hermite b-ensembles by roots of orthogonal polynomials.
  • Steland, A.
    On the distribution of the clipping median under a mixture model.
  • Dette, H. and Hetzler, B.
    Specification tests indexed by bandwidths.
  • Bart, A. G., Bart, V. A., Steland, A. and Zaslavskiy, M. L.
    Modeling disease dynamics and survivor functions by sanogenesis curves.
  • Braess, D. and Dette, H.
    The asymptotic minimax risk for the estimation of constrained binomial and multinomial probabilities.
    PS
  • Steland, A.
    Random walks with drift - A sequential view.
  • Barndorff-Nielsen, O. E., Graversen, S. E., Jacod, J., Podolskij, M. and Shephard, N.
    A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales.
  • Biedermann, S., Dette, H. and Zhu, W.
    Optimal designs for dose-response models with restricted design spaces.
  • Neumeyer, N., Dette, H. and Nagel, E.-R.
    Bootstrap tests for the error distribution in linear and nonparametric regression models.
  • Dette, H., Podolskij, M. and Vetter, M.
    Estimation of integrated volatility in continuous time financial models with applications to goodness-of-fit testing.
  • Dette, H., Wong, W. K. and Zhu, W.
    On the Equivalence of Optimality Design Criteria for the Placebo-Treatment Problem.
  • Munk, A., Neumeyer, N. and Scholz, A.
    Nonparametric Analysis of Covariance - the Case of Inhomogeneous and Heteroscedastic Noise.
  • Dette, H., Melas, V. B. and Wong, W. K.
    Optimal design for goodness-of-fit of the Michaelis-Menten enzyme kinetic function.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Optimal designs for 3D shape analysis with spherical harmonic descriptors.
  • Dette, H. and Pilz, K. F.
    On the estimation of a monotone conditional variance in nonparametric regression.
  • Dette, H. and Pilz, K. F.
    A comparative study of monotone nonparametric kernel estimates.
  • Biedermann, S., Dette, H. and Pepelyshev, A.
    Some robust design strategies for percentile estimation in binary response models.
  • Bachmann, D. and Dette, H.
    A note on the Bickel-Rosenblatt test in autoregressive time series.
  • Dette, H., Melas, V. B. and Wong, W. K.
    Locally D-optimal Designs for Exponential Regression.
  • Lopez, I. M., Ortiz Rodriguez, I. M., Pepelyshev, A. and Dette, H.
    Efficient design of experiment for exponential regression models.
  • Melas, V. B.
    On the functional approach to optimal designs for nonlinear models.

2003

  • Birke, M. and Dette, H.
    A note on testing the covariance matrix for large dimension.
  • Neumeyer, N., Pilz, K. F. and Dette, H.
    A note on nonparametric estimation of the effective dose in quantal bioassay.
  • Dette, H., Melas, V. B. and Strigul, N.
    Design of experiments for microbiological models.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Locally E-optimal designs for exponential regression models.
  • Dette, H., Haines, L. M. and Imhof, L. A.
    Bayesian and maximin optimal designs for heteroscedastic regression models.
  • Biedermann, S., Dette, H. and Pepelyshev, A.
    Maximin Optimal Designs for the Compartmental Model.
  • Dette, H. and Kwiecien, R.
    Finite sample performance of sequential designs for model identification.
  • Biedermann, S. and Dette, H.
    Numerical Construction of Maximin Optimal Designs for Binary Response Models.
  • Dette, H., Neumeyer, N. and Pilz, K. F.
    A simple nonparametric estimator of a monotone regression function.
  • Dette, H., Nagel, E.-R. and Neumeyer, N.
    A note on testing symmetry of the error distribution in linear regression models.
  • Steland, A.
    Optimal sequential kernel smoothers under local nonparametric alternatives for dependent processes.
  • Pawlak, M., Rafajlowicz, E. and Steland, A.
    On detecting jumps in time series - Nonparametric setting.
  • Zhang, C. and Dette, H.
    A Power Comparison Between Nonparametric Regression Tests.
  • O'Brien, T. E. and Dette, H.
    Efficient experimental design for the Behrens-Fisher problem with application to bioassay.
  • Neumeyer, N. and Sperlich, S.
    Comparison of Separable Components in Different Samples.
  • Steland, A.
    Sequential control of time series by functionals of kernel-weighted empirical processes under local alternatives.
  • Dette, H., Haines, L. M and Imhof, L. A.
    Maximin and Bayesian optimal designs for regression models.
  • Neumeyer, N. and Dette, H.
    Testing for symmetric error distribution in nonparametric regression models.
  • Studden, W. J. and Dette, H.
    A note on the maximization of matrix valued Hankel determinants with applications.
  • Dette, H.
    On robust and efficient designs for risk estimation in epidemiologic studies.
  • Biedermann, S. and Dette, H.
    A note on maximin and Bayesian D-optimal designs in weighted polynomial regression.

2002

  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Optimal designs for a class of nonlinear regression models.
  • Neumeyer, N. and Dette, H.
    A note on one-sided nonparametric analysis of covariance by ranking residuals.
  • Dette, H. and Studden, W. J.
    A note on the matrix valued q-d algorithm and matrix orthogonal polynomials on [0,1].
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    Standardized maximin E-optimal design for the Michaelis Menten model.
  • Dette, H., Haines, L. M. and Imhof, L. A.
    Maximin and Bayesian optimal designs for linear and non-linear regression models.
  • Dette, H. and Studden, W. J.
    Quadrature formulas for matrix measures -- a geometric appoach.
  • Dette, H., Melas, V. B., Pepelyshev, A. and Strigul, N.
    Efficient design of experiments in the Monod model.
  • Neumeyer, N.
    A central limit theorem for two-sample U-processes.
  • Dette, H.
    Canonical moments, orthogonal polynomials with application to statistics.
  • Dette, H. and Biedermann, S.
    Robust and efficient designs for the Michaelis-Menten model.
  • Dette, H. and Munk, A.
    Some Methodological Aspects of Validation of Models in Nonparametric Regression.

2001

  • Dette, H. and Spreckelsen, I.
    A note on a specification test for time series models based on spectral density estimation.
  • Dette, H.
    Strong Approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials.
  • Dette, H. and Spreckelsen, I.
    Some comments on specification tests in nonparametric absolutely regular processes.
  • Dette, H. and Grigoriev, Y.
    A unified asymptotic expansion for distributions of quadratic functionals in nonlinear regression models.
  • Dette, H., Kusi-Appiah, S. and Neumeyer, N.
    Testing symmetry in nonparametric regression models.
  • Dette, H. von Lieres und Wilkau, C. and Sperlich, S.
    A comparison of different nonparametric methods for inference on additive models.
  • Dette, H., Song, D. and Wong, W. K.
    Robustness properties of minimally-supported Bayesian D-optimal designs for heteroscedastic models.
  • Dette, H., Melas, V. B. and Biedermann, S.
    A functional-algebraic determination of D-optimal designs for trigonometric regression models on a partial circle.
  • Dette, H. and von Lieres und Wilkau, C.
    On a test for constant volatility in continuous time financial models.
  • Dette, H., Melas, V. B. and Pepelyshev, A.
    D-optimal designs for trigonometric regression models on a partial circle.
  • Steland, A.
    On Jump-Preserving Sequential Control for Certain Mixing Processes with Applications in Finance and Econometrics.
  • Dette, H. and Studden, W. J.
    Matrix Measures, Moment Spaces and Favard's Theorem for the Interval [0,1] and [0,\infty).
  • Antille, G., Dette, H. and Weinberg, A.
    A note on optimal designs in weighted polynomial regression for the classical efficiency functions.
  • Dette, H. and Melas V. B.
    Optimal designs for estimating individual coefficients in Fourier regression models.

2000

  • Dette, H. and Neumeyer, N.
    Nonparametric comparison of regression curves - an empirical process approach.
  • Dette, H. and Melas, V. B.
    Optimal designs for estimating individual coefficients in polynomial regression - a functional approach.
  • Biedermann, S. and Dette, H.
    Minimax optimal designs for nonparametric regression - a further optimality property of the uniform distribution.
  • Dette, H. and Neumeyer, N.
    Non-parametric analysis of covariance.
  • Steland, A.
    Detecting Fast-Varying Drifts of Financial Time Series by Jump-Preserving Nonparametric Control Charts.
  • Schmid, W. and Steland, A.
    Sequential Control of Non-Stationary Processes by Nonparametric Kernel Control Charts.
  • Biedermann, S. and Dette, H.
    Optimal designs for testing the functional form of a regression via nonparametric estimation techniques.
  • Dette, H.
    A consistent test for heteroscedasticity in nonparametric regression based on the kernel method.
  • Dette, H. and Franke, T.
    Constrained D- and D1-optimal designs for polynomial regression.
  • Dette, H. and Franke, F.
    Robust designs for polynomial regression by maximizing a minimum of D-and D1-efficiencies.
  • Biedermann, S. and Dette, H.
    Testing linearity of regression models with dependent errors by kernel based methods.
  • Munk, A. and Ruymgaart, F.
    Minimax rates for estimating the variance and its derivatives in nonparametric regression - an application of the van Trees inequality.
  • Dette, H. and von Lieres und Wilkau, C.
    Testing additivity by kernel based methods - what is a reasonable test?

1999

  • Dette, H., Haines, L. M. and Imhof, L. A.
    Optimal Designs for Rational Models and Weighted Polynomial Regression.
  • Dette, H.
    On a nonparametric test for linear relationships.
  • Dette, H.
    First return probabilities of birth and death chains and associated orthogonal polynomials.
  • Munk, A.
    Connections Between Average and Individual Bioequivalence.
  • Czado, C. and Munk, A.
    Noncanonical Links in Generalized Linear Models - When is the Effort Justified?
  • Munk, A. and Czado, C.
    A Completely Nonparametric Approach to Population Bioequivalence in Crossover Trials.
  • Munk, A.
    Testing the goodness of fit of parametric regression models with random Toeplitz forms.
  • Munk, A.
    An unbiased test for the average equivalence problem - the small sample case.
  • Munk, A.
    Optimal Inference for Circular Variation Diminishing Experiments with Applications to the von Mises Distribution and the Fisher-Efron Parabola Model.
  • Steland, A.
    On Robust GMM Estimation with Applications in Economics and Finance.
  • Steland, A.
    Ordinal Regression Based on the Rank Modeling Approach.

1998

  • Dette, H. and O'Brien, T. E.
    Optimal Criteria for Regression Models based on Predicted Variance.
  • Munk, A.
    A note on Unbiased Testing for the Bioequivalence Problem - another Christmas Tree.
  • Dette, H. and Wong, W. K.
    E-Optimal Designs for the Michaelis-Menten Model.
  • Dette, H. and Lo Huang, M.-N.
    Convex Optimal designs for Compound Polynomial Extrapolation.
  • Dette, H. and Grigoriev, Y.
    A unified approach to Second Order Optimality Criteria in Nonlinear Design of Experiments.
  • Dette, H.
    A Consistent Test for the Functional Form of a Regression based on a Difference of Variance Estimators.
  • Derbort, S. and Dette, H.
    Analysis of Variance in Nonparametric Regression Models.
  • Dette, H. and Spreckelsen, I.
    A Test for Randomness against ARMA Alternatives.
  • Munk, A. and Pflüger, R.
    1-alpha Equivariant Confidence Rules for Convex Alternatives are alpha/2-Level Tests - with Applications to the Multivariate Assessment of Bioequivalence.

1997

  • Dette, H., Munk, A. and Wagner, T.
    Estimating the Variance in Nonparametric Regression by Quadratic Forms - what is a reasonable choice?
  • Dette, H., Munk, A. and Wagner, T.
    A review of Variance Estimators with extensions to Multivariate Nonparametric Regression Models.
  • Dette, H. and Munk, A.
    Testing Heteroscedasticity in Nonparametric Regression.
  • Munk, A.
    Optimal Inference for the von Mises Distribution with Applications to Efron's Parabola Model.
  • Brunner, E., Dette, H. and Munk, A.
    Box-type Approximations in Nonparametric Factorial Designs.
  • Dette, H. and Sahm, M.
    Standardized Optimal Designs for Binary Response Experiments.
  • Dette, H. and Haller, G.
    Optimal Discriminating Designs for Fourier Regression.
  • Dette, H.
    Some Applications of Canonical Moments in Fourier Regression Models.
  • Munk, A.
    Tchebycheff-Experiments.
  • Dette, H. and Sahm, M.
    Minimax Optimal Designs in Nonlinear Regression Models.
  • Dette, H. and Wong, W. K.
    Optimal Designs for Modeling Response's Variance as a Function of the Mean.
  • Dette, H. and Wong, W. K.
    Bayesian Optimal Designs for Models with an Exponential Efficiency Function on a Compact Design Space.
  • Dette, H., Munk, A. and Wagner, T.
    Testing Model Assumptions in Multivariate Linear Regression Models.
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