Deutsche Version
News

Graduate School Scholarship Programme: The Department of Mathematics in co-operation with the German Academic Exchange Service (DAAD), invites applications for two scholarships for international doctoral candidates. Application deadline is January 10, 2018. More information is available here.


Next talk in the Stochastics Colloquium:
20.12.2017, 11:00, Dr. Nina Miolane (GeomStats Team at Inria/Stanford)

"Template shape estimation: correcting an asymptotic bias" (Abstract).
Statistics Meets Friends: The workshop "Statistics Meets Friends - from biophysics to inverse problems and back -" took place in Göttingen from November 29th to December 1st, 2017.
Press release: Statistics Meets Friends - from biophysics to inverse problems and back.
Press release: Dr. Vlada Limic, CNRS Strasbourg, has received the Friedrich Wilhelm Bessel Research Award of the Alexander von Humboldt Foundation. She is doing research at the Institute for Mathematical Stochastics for one year. Her host is Prof. Dr. Anja Sturm (press release).
publications

Research Group "Applied and Mathematical Statistics"
Publications: Prof. Dr. A. Munk

  • Behr, M., Munk, A. (2017).
    Minimax estimation in linear models with unknown finite alphabet design arxiv.org/abs/1711.04145. Submitted.
  • Li, H., Guo, Q., Munk, A. (2017).
    Multiscale change-point segmentation: Beyond step functions arxiv.org 1708.03942. Submitted.
  • Tameling, C., Sommerfeld, M., Munk, A. (2017).
    Empirical optimal transport on countable metric spaces: Distributional limits and statistical applications arXiv:1707.00973. Submitted.
  • Singer, M., Krivobokova, T., Munk, A. (2017).
    Kernel partial least squares for stationary data. Journ. Mach. Learn. Research, 18(123), 1-41.
  • Pein, F., Tecuapetla-Gómez, I., Schütte, O. M., Steinem, C., Munk, A. (2017).
    Fully-Automatic Multiresolution Idealization for Filtered Ion Channel Recordings: Flickering Event Detection arxiv.org 1706.03671. Submitted.
  • Proksch, K., Werner, F., Munk, A. (2017).
    Multiscale scanning in inverse problems. arxiv.org/abs/1611.04537, The Annals of Statistics. To appear.
  • Mütze, T., Konietschke, F., Munk, A., Friede, T. (2017).
    A studentized permutation test for three-arm trials in the "gold standard" design. Statistics in Medicine, 36, 883-898.
  • Sommerfeld, M. , Munk, A. (2017).
    Inference for empirical Wasserstein distances on finite spaces. arxiv.org/abs/1610.03287, Journ. Royal. Statist. Soc. Ser. B. To appear.
  • Behr, M., Holmes, C., Munk, A. (2017).
    Multiscale blind source separation. The Annals of Statistics, arXiv:1608.07173. To appear.
  • Grasmair, M., Li, H., Munk, A. (2017).
    Variational multiscale nonparametric regression: smooth functions Annales de l’Institute Henri Poincare (B), Probabilités et Statistiques, arxiv.org 1512.01068. To appear.
  • Behr, M., Munk, A. (2017).
    Identifiability for blind source separation of multiple finite alphabet linear mixtures. IEEE Trans. Inf. Theory, 63(9), 5506 - 5517.
  • Pein, F., Sieling, H., Munk, A. (2017).
    Heterogeneuous change point inference (R package: HSMUCE). arxiv.org 1505.04898, Journ. Royal. Statist. Soc. Ser. B, 79, 1207–1227.
  • Enikeeva, F., Munk, A., Werner, F. (2017).
    Bump detection in heterogeneous Gaussian regression. Bernoulli 2018, 24, 2, 1266-1306.
  • Bauer, U., Munk, A., Sieling, H., Wardetzky, M. (2017).
    Persistence barcodes versus Kolmogorov signatures: Detecting modes of one-dimensional signals. Foundations of Computational Mathematics, 17, 1-33.
  • Li, H., Munk, A., Sieling, H., Walther, G. (2016).
    The essential histogram arxiv.org 1612.07216. Submitted.
  • Singer, M., Krivobokova, T., Munk, A., de Groot, B., L. (2016).
    Partial least squares for dependent data. Biometrika, 103, 351-362.
  • Hafi, N., Grunwald, M., van den Heuvel, L. S., Aspelmeier, T., Chen, J.-H., Zagrebelsky, M., Schuette, O. M., Steinem, C., Korte, M., Munk, A., Walla, J. P. (2016).
    Corrigendum: Fluorescence nanoscopy by polarization modulation and polarization angle narrowing. Nature Methods, 13, 101.
  • Hafi, N., Grunwald, M., van den Heuvel, l.S., Aspelmeier, T., Steinem, C., Korte, M., Munk, A., Walla, J.P. (2016).
    Reply to "Polarization modulation adds little additional information to super-resolution fluorescence microscopy" Nature Methods, 13, 8-9.
  • Mütze, T., Munk, A., Friede, T. (2016).
    Design and analysis of three‐arm trials with negative binomially distributed endpoints. Statistics in Medicine, 35, 505 - 521.
  • Rippl, T., Munk, A., Sturm, A. (2016).
    Limit laws of the empirical Wasserstein distance: Gaussian distributions. Journal of Multivariate Analysis, 151, 90-109.
  • Tecuapetla-Gómez, I., Munk, A. (2016).
    Autocovariance estimation in regression with a discontinuous signal and m-dependent errors: A difference-based approach (R package: dbacf). Scandinavian Journal of Statistics (arxiv.org 1507.02485v4). Accepted.
  • Li, H., Munk, A., Sieling, H. (2016).
    FDR-control in multiscale change-point segmentation. Electron. J. Statist., 10(1), 918-959.
  • Huckemann, S.F., Kim. K.-R., Munk, A., Rehfeld, F., Sommerfeld, M., Weickert, J., Wollnik, C. (2016).
    The circular SiZer, inferred persistence of shape parameters and application to stem cell stress fibre structures. Bernoulli, arxiv.org 1404.3300, 22, 2113-2142.
  • Hartmann, A., Huckemann, S., Dannemann, J., Laitenberger, O., Geisler, C., Egner, A., Munk, A. (2016).
    Drift estimation in sparse sequential dynamic imaging: with application to nanoscale fluorescence microscopy. J. Royal Statist. Society, Ser. B, arxiv.org 1403.1389, 78(3), 563–587.
  • Ta, H., Keller, J., Haltmeier, M. Saka, S.K., Schmied, J., Opazo, F., Tinnefeld, P., Munk, A., Hell, S.W. (2015).
    Mapping molecules in scanning far-field fluorescence nanoscopy. Nature Communications, 6, 1-7, DOI: 10.1038/ncomms8977.
  • Munk, A., Werner, F. (2015).
    Discussion of “Hypotheses testing by convex optimization” Electron. J. Statist., 9(2), 1720-1722.
  • Peter, P., Weickert,J., Munk, A., Krivobokova, T., Li, H. (2015).
    Justifying tensor-driven diffusion from structure-adaptive statistics of natural images. Energy Minimization Methods in Computer Vision and Pattern Recognition, 8932, 263--277.
  • Aspelmeier, T., Egner, A., Munk, A. (2015).
    Modern Statistical Challenges in High Resolution Fluorescence Microscopy. Annual Review of Statistics and its Application, 2, 163-202.
  • Sabel, T., Schmidt-Hieber, J., Munk, A. (2015).
    Spot volatility estimation for high-frequency data: adaptive estimation in practice. Springer Lecture Notes in Statistics: Modeling and Stochastic Learning for Forecasting in High Dimension, 213-241.
  • Tams, B. and Mihailescu, P. and Munk, A. (2015).
    Security Considerations in Minutiae-based Fuzzy Vaults. IEEE Transactions on Information Forensics and Security, 10, 985 - 998 (Preprint).
  • Hafi, N., Grunwald, M., van den Heuvel, L.S., Aspelmeier, T., Chen, J.-H., Zagrebelsky, M., Schütte, O.M., Steinem, C., Korte, M., Munk, A., Walla, P.J. (2014).
    Fluorescence nanoscopy by polarization modulation and polarization angle narrowing. Nature Methods, 11, doi: 10.1038/nmeth.2919.
  • Futschik, A., Hotz, T., Munk, A., Sieling, H. (2014).
    Multiscale DNA partitioning: statistical evidence for segments. Bioinformatics, doi: 10.1093/bioinformatics/btu180 (Preprint).
  • Greb, F., Krivobokova, T., Munk, A., von Cramon-Taubadel, S. (2014).
    Regularized Bayesian estimation of generalized threshold regression models. Bayesian Analysis, 9(1), 171-196 (Preprint).
  • Frick, S., Hohage, T., Munk, A. (2014).
    Asymptotic laws for change point estimation in inverse regression. Statistica Sinica, 24, 555-575 (Preprint).
  • Frick, K., Munk, A., Sieling, H. (2014).
    Multiscale Change-Point Inference (software "stepR" for multiscale change point analysis "SMUCE") With discussion and rejoinder by the authors. Journ. Royal Statist. Society, Ser. B, , 76, 495-580. arXiv:1301.7212 long version with full proofs.
  • Haltmeier, M., Munk, A. (2014).
    Extreme value analysis of empirical frame coefficients and implications for denoising by soft-thresholding. Applied and Computational Harmonic Analysis, 36 (3), 434–460.
  • Greb, F., von Cramon-Taubadel, S., Krivobokova, T., Munk, A. (2013).
    The estimation of threshold models in price transmission analysis. American Journal of Agricultural Economics, 95, 900-916.
  • Yalunin, S. V., Herink, G., Solli, D. R., Krüger, M., Hommelhoff, P., Diehn, M., Munk, A., Ropers, C. (2013).
    Field localization and rescattering in tip-enhanced photoemission. Ann. Phys., 525, L12-L18.
  • Li, H., Haltmeier, M., Zhang, S., Frahm, J., Munk, A. (2013).
    Aggregated Motion Estimation for Image Reconstruction in Real-Time MRI (Supplements). Magnetic Resonance in Medicine, DOI: 10.1002/mrm.25020.
  • Friede, T., Kombrink, K., Munk, A. (2013).
    Design and semiparametric analysis of non-inferiority trials with active and placebo control for censored time to event data Statistics in Medicine, 32, 3055-3066.
  • Hotz,T., Schütte, O., Sieling, H., Polupanow, T., Diederichsen, U., Steinem, C., Munk, A. (2013).
    Idealizing ion channel recordings by jump segmentation and statistical multiresolution analysis IEEE Trans. on NanoBioScience, 12, 376-386. (Preprint).
  • Frick,K. Marnitz,P. Munk,A. (2013).
    Statistical Multiresolution Estimation for Variational Imaging: With an Application in Poisson-Biophotonics. J. Math. Imaging Vision, 46(3), 370-387.
  • Schmidt-Hieber, J., Munk, A., Duembgen, L. (2013).
    Multiscale Methods for Shape Constraints in Deconvolution: Confidence Statements for Qualitative Features. Annals of Statistics, 41, 1299-1328 (Preprint).
  • Krivobokova, T., Briones, R., Hub, J., Munk, A., de Groot, B. (2012).
    Partial least squares functional mode analysis: application to membrane proteins AQP1, Aqy1 and CLC-ec1 Biophysical Journal, 103, 786-796.
  • Geisler, C., Hotz, T., Schönle, A., Hell, S. W., Munk, A., Egner, A. (2012).
    Drift estimation for single marker switching based imaging schemes. Optics Express, 20 (7), 7274-7289.
  • Hotz, T., Marnitz, P., Stichtenoth, R., Davies, L., Kabluchko, Z., Munk, A. (2012).
    Locally adaptive image denoising by a statistical multiresolution criterion. Comp. Stat. Data Anal., 56(3), 543-558.
  • Frick, K., Marnitz, P., Munk, A. (2012).
    Statistical Multiresolution Dantzig Estimation in Imaging: Fundamental Concepts and Algorithmic Framework Electron. J. Stat., 6, 231-268.
  • Hoffmann, M., Munk, A., Schmidt-Hieber, J. (2012).
    Adaptive wavelet estimation of the diffusion coefficient under additive error measurements. Annales de l’Institute Henri Poincare, 48, 1186--1216 (Preprint).
  • Frick, K., Marnitz, P., Munk, A. (2012).
    Shape Constrained Regularisation by Statistical Multiresolution for Inverse Problems Inverse Problems, 28, 065006.
  • Hotz, T., Gottschlich, C., Lorenz, R., Bernhardt, S., Hantschel, M., Munk, A. (2011).
    Statistical Analyses of Fingerprint Growth. BIOSIG 2011 - Proceedings - International Conference of the Biometrics Special Interest Group, 08.-09. September 2011 in Darmstadt, Germany. Lecture Notes in Informatics, P-191, 11-20.
  • Gottschlich, C., Hotz, T., Lorenz, R., Bernhardt, S., Hantschel, M., Munk, A. (2011).
    Modeling the Growth of Fingerprints Improves Matching for Adolescents IEEE Transactions on Information Forensics and Security, 6(3), 1165-1169.
  • Munk, A. , Stockis, J.P., Valeinis, J., Giese, G. (2011).
    Neyman smooth goodness of fit tests for the marginal distribution of dependent data. Ann. Inst. Statist. Math. , 63, 639-659.
  • Dannemann, J., Munk, A. (2010).
    Discussion of "Maximum likelihood estimation of a multi-dimensional log-concave density" by Cule, Samworth and Stewart. J. Royal Statist. Society, Ser. B, 72, 593-595.
  • Munk, A., Schmidt-Hieber, J. (2010).
    Lower bounds for volatility estimation in microstructure noise models. Borrowing Strength: Theory Powering Applications - A Festschrift for Lawrence D. Brown, IMS Collections, 6, 43-55 To appear (Preprint).
  • Huckemann, S., Hotz, T., Munk, A. (2010).
    Intrinsic shape analysis: Geodesic principal component analysis for Riemannian manifolds modulo Lie group actions. Discussion paper with rejoinder. Statistica Sinica, 20, 1-100 (Preprint).
  • Munk, A., Pricop, M. (2010).
    On the self-regularization property of the EM algorithm for Poisson inverse problems. Statistical Modelling and Regression Structures. Festschrift in Honour of Luwdig Fahrmeir. (Eds.) T. Kneib, G. Tutz, 431-446.
  • Mielke, M., Munk, A. (2010).
    The assessment and planning of non-inferiority trials for retention of effect hypotheses - towards a general approach. arXiv:0912.4169v1 [stat.ME]. In revision.
  • Huckemann, S., Kim, P., Koo, J.-Y., Munk, A. (2010).
    Moebius deconvolution on the hyperbolic plane with application to impedance density estimation. Ann. Statist., 38 (4), 2465-2498 (Preprint).
  • Munk, A., Schmidt-Hieber, J. (2010).
    Nonparametric estimation of the volatility function in a high-frequency model corrupted by noise. Electronic Journal of Statistics, 4, 781-821 (Preprint).
  • Hotz, T., Huckemann, S., Gaffrey, D., Munk, A., Sloboda, B. (2010).
    Shape spaces for pre-alingend star-shaped objects in studying the growth of plants. Journal of the Royal Statistical Society, Series C (Applied Statistics), 59 (1), 127-143 (Preprint).
  • Huckemann, S., Hotz, T., Munk, A. (2010).
    Intrinsic MANOVA for Riemannian Manifolds with an Application to Kendalls Spaces of Planar Shapes. IEEE Trans. Patt. Anal. Mach. Intell., 32 (4), 593-603, "Spotlight Paper" for this issue with its "Special Section on Shape Analysis and its Applications in Image Understanding", freely available until 18 March 2010 (Preprint).
  • Cai, T. T., Munk, A., Schmidt-Hieber, J. (2010).
    Sharp minimax estimation of the variance of Brownian motion corrupted with Gaussian noise. (Including Supplementary material). Statistica Sinica, 20, 1011-1024 (Preprint).
  • Huckemann, S., Hotz, T., Munk, A. (2010).
    Rejoinder on "Intrinsic shape analysis: Geodesic principal component analysis for Riemannian manifolds modulo Lie group actions." Statistica Sinica, 20, 1-100 (Preprint).
  • Mihailescu, P. and Munk, A. and Tams B. (2009).
    The fuzzy vault for fingerprints is vulnerable to brute force attack. in Proc. BIOSIG 2009, ser. LNI, vol. 155, pp. 43-45.
  • Huckemann, S., Hotz, T., Munk, A. (2009).
    Intrinsic two-way MANOVA for shape spaces. Proc. of the ISI2009, article.
  • Balabdaoui, F., Mielke, M., Munk, A. (2009).
    The likelihood ratio test for non-standard hypotheses near the boundary of the null - with application to the assessment of non-inferiority. Statistics & Decisions, 27, 75-92.
  • Munk, A., Schmidt-Hieber, J. (2009).
    The Estimation of Different Scales in Microstructure Noise Models from a Nonparametric Regression Perspective Oberwolfach Reports, 6, 2210-2212.
  • Gottschlich, C., Mihailescu, P., Munk, A. (2009).
    Robust Orientation Field Estimation in Fingerprint Images with Broken Ridge Lines Proc. Image and Signal Processing and Analysis (ISPA), 529-533.
  • Gottschlich, C., Mihailescu, P., Munk, A. (2009).
    Robust Orientation Field Estimation and Extrapolation Using Semilocal Line Sensors IEEE Transactions on Information Forensics and Security, 4(4), 802-811.
  • Bauer, F., Hohage, T., Munk, A. (2009).
    Iteratively regularized Gauss-Newton method for nonlinear inverse problems with random noise SIAM J. Num. Anal. , 47, 1827-1846 (Preprint).
  • Kabluchko, Z., Munk, A. (2009).
    Shao s theorem on the maximum of standardized random walk increments for multidimensional arrays. ESAIM Prob. Stat., 13, 409-416 (Preprint).
  • Bissantz, N., Claeskens, G., Holzmann, H., Munk, A. (2009).
    Testing for lack of fit in inverse regression -- with applications to biophotonic imaging. J. Royal Statist. Soc. Ser. B, 71(1), 25-48 (Preprint).
  • Boysen, L., Bruns, S., Munk, A. (2009).
    Jump estimation in inverse regression. Elect.ronic J. Statist. , 3, 1322-1359 (Preprint).
  • Bissantz, N., Dümbgen, L., Munk, A., Stratmann, B. (2009).
    Convergence analysis of generalized iteratively reweighted least squares algorithms on convex function spaces.SIAM J. Optimization, 19, 1828-45.
  • Boysen, L., Kempe, A., Munk, A., Liebscher, V., Wittich, O. (2009).
    Consistencies and rates of convergence of jump penalized least squares estimators. Ann. Statist., 37, 157-183 (Preprint).
  • Bissantz, N., Mair, B., Munk, A. (2008).
    A statistical stopping rule for MLEM reconstructions in PET. IEEE Nucl. Sci. Symp. Conf. Rec., 8, 4198-4200.
  • Mieloch, K., Munk, A., Mihailescu, P. (2008).
    Hierarchically linked extended features in fingerprints. Proc. of the 6th Biometrics Symposium 2008 (BSYM) , 47-52 (Preprint).
  • Dümbgen, L., Igl, B.W., Munk, A. (2008).
    P-values for classification. Electronic J. Stat., 2, 468-493 (Preprint).
  • Kabluchko, Z., Munk, A. (2008).
    Exact convergence rate for the maximum of standardized Gaussian increments. Elect. Comm. in Probab., 13, 302-310. Abstract and PDF.
  • Mielke, M., Munk, A., Schacht, A. (2008).
    Technical Report on "The assessment of non-inferiority in a gold standard design with censored, exponentially distributed endpoints". (Preprint).
  • Lakomek, N.A., Walter, K., Fares, C., Lange, O., de Groot, B., Grubmuller, H., Bruschweiler, R., Munk, A., Becker, S., Meiler, J., Griesinger, C. (2008).
    Self-consistent residual dipolar coupling based model-free analysis for the robust determination of nanosecond to microsecond protein dynamics. Journal of Biomolecular NMR, 41, 139-155, (supplement ) (Preprint).
  • Holzmann, H., Munk, A. (2008).
    Reply to Reader Reacton: On the nonidentifiability of population sizes Biometrics, 64, 979-981.
  • Huckemann, S., Hotz, T., Munk, A. (2008).
    Global Models for the Orientation Field of Fingerprints: An Approach Based on Quadratic Differentials. IEEE Trans. Patt. Anal. Mach. Intell., 30(9), 1507-1519 (Preprint).
  • Mielke, M., Munk, A., Schacht, A. (2008).
    The assessment of non-inferiority in a gold standard design with censored, exponentially distributed endpoints. Statistics in Medicine, 27, 5093-5110.
  • Munk, A., Paige, R., Pang, J., Patrangenaru, V., Ruymgaart, F. (2008).
    The one- and multi-sample problem for functional data with application to projective shape analysis. J. Multivariate Analysis, 99, 815-833 (Preprint).
  • Bauer, F., Munk, A. (2007).
    Optimal regularization for ill-posed problems in metric spaces. J. Inverse and Ill-Posed Problems, 15, 137-148 (Preprint).
  • Bissantz, N., Dümbgen, L., Holzmann, H. and Munk, A. (2007).
    Nonparametric confidence bands in deconvolution density estimation. J. Royal Statist. Society Ser. B., 69, 483-506.
  • Boysen, L., Liebscher, V., Munk, A., Wittich, O. (2007).
    Scale Space Consistency of Piecewise Constant Least Squares Estimators - Another Look at the Regressogram. IMS Lecture Notes Series, 55, 65-84 (Preprint).
  • Munk, A. Neumeyer, N., Scholz, A. (2007).
    Nonparametric analysis of covariance - the case of inhomogeneous and heteroscedastic noise Scand. J. Statist., 34, 511-534 (Preprint).
  • Bissantz, N., Hohage, T., Munk, A., Ruymgaart, F. (2007).
    Convergence rates of general regularization methods for statistical inverse problems and applications. SIAM J. Numerical Analysis, 45, 2610-2636. (Preprint).
  • Holzmann, H., Bissantz, N. und Munk, A. (2007).
    Density testing in a contaminated sample J. Multivariate Analysis, 98, 57-75. (Preprint).
  • Munk, A., Mielke, M., Skipka, G., Freitag, G. (2007).
    Testing noninferiority in three-armed clinical trials based on the likelihood ratio statistics. Canad. J. Statist., 35, 413-431.
  • Freitag, G., Czado, C., Munk, A. (2007).
    A nonparametric test for similarity of marginals - with applications to the assessment of population bioequivalence. J. Statist. Plann. Inf., 137, 697-711 (Preprint).
  • Mihailescu, P., Mieloch, K., Munk A. (2006).
    Fingerprint classification using entropy sensitive tracing. Progress in Industrial Mathematics at ECMI 2006, 928-934 (Preprint).
  • Holzmann, H., Munk, A. Zucchini, W. (2006).
    On Identifiability in Capture-Recapture Models: Supporting Material--Proofs. Biometrics 62, supporting material. (Preprint).
  • N. Bissantz, B. Mair, A. Munk (2006).
    A multi-scale stopping criterion for MLEM reconstructions in PET. IEEE Nucl. Sci. Symp. Conf. Rec., 6, 3376-3379 (Preprint).
  • Holzmann, H., Munk, A., Gneiting, T. (2006).
    Identifiability of finite mixtures of elliptical distributions. Scand. J. Statist., 33, 753-764 (Preprint).
  • Biedermann, S., Nagel, E., Munk, A., Holzmann, H., Steland, A. (2006).
    Tests in a case-control design including relatives Scand. J. Statist., 33, 621-636 (Preprint).
  • Holzmann, H., Munk, A., Zucchini, W. (2006).
    On identifiability in capture-recapture models. Biometrics, 62, 934-936. (Preprint).
  • Freitag, G., Lange, S., Munk, A. (2006).
    Nonparametric assessment of noninferiority with censored data. Statistics in Medicine, 25, 1201-1217.
  • Holzmann, H., Munk, A., Suster, M., Zucchini, W. (2006).
    Hidden Markov models for circular and linear-circular time series. Environmental and Ecological Statistics (Special Issue on Analyses of Directional Data in Ecological and Environmental Sciences)., 13 (3), 325-347 (Preprint).
  • Freitag, G., Munk, A. (2005).
    Consistency of bootstrap procedures for the nonparametric assessment of noninferiority with random censorship. Technical Report. (Preprint).
  • Mieloch, K., Mihailescu, P., Munk, A. (2005).
    Dynamic threshold using polynomial surface regression with application to the binarisation of fingerprints. Proc. of SPIE, Biometric Technology for Human Identification II, 5779, 94-104 (Preprint).
  • Bissantz, N., Holzmann, H. Munk, A. (2005).
    Testing parametric assumptions on band- or time-limited signals under noise. IEEE Transactions on Information Theory, 51, 3796-3805 (Preprint).
  • Munk, A., Skipka, G., Stratmann, B. (2005).
    Testing general hypotheses under binomial sampling: The two sample case - asymptotic theory and exact procedures. Comp. Stat. Data Analysis, 94/3, 723-739 (Preprint).
  • Munk, A., Bissantz, N., Wagner, T., Freitag, G. (2005).
    On difference based variance estimation in nonparametric regression when the covariate is high dimensional. J. Roy. Statist. Soc. Ser. B, 67, 19-41.
  • Freitag, G., Munk, A. (2005).
    On Hadamard differentiability in k-sample semiparametric models - with applications to the assessment of structural relationships. Journ. Multiv. Analysis, 94, 123-158.
  • Bissantz, N., Hohage, T., Munk, A. (2004).
    Consistency and rates of convergence of nonlinear Tikhonov regularisation with random noise. Inverse Problems, 20, 1773-89.
  • Munk, A., Ruymgaart, F. (2004).
    Discussion of ``Wavelet deconvolution in a periodic setting'' by I.M. Johnstone, G. Kerkyacharian, D. Picard and M. Raimondo. J. Royal Statist. Soc. Ser. B, 66, 642-43.
  • Holzmann, H., Munk, A., Stratmann, B. (2004).
    Identifiability of finite mixtures - with applications to circular distributions. Sankhya, 66, 440-450 (Preprint).
  • Skipka, G., Munk, A., Freitag, G. (2004).
    Unconditional exact tests for the difference of binomial probabilities - contrasted and compared. Comp. Stat. Data Analysis, 47, 757-773.
  • Bissantz, N., Munk, A., Scholz, A. (2003).
    Parametric versus non-parametric modelling? Statistical evidence based on P-value curves. Mon. Not. R. Astron. Soc., 340, 1190-1198.
  • Dette, H., Munk, A. (2003).
    Some methodological aspects of validation of models in nonparametric regression. Statistica Neerlandica, 57, 207-244.
  • Freitag, G., Munk, A., Vogt, M. (2003).
    Assessing structural relationships between distributions - a quantile process approach based on Mallow's distance. In: Recent Advances and Trends in Nonparametric Statistics. Ed.: Akritas, M. G., Politis, D. N., Amsterdam: Elsevier B. V., 123-137.
  • Freitag, G., Munk, A., Hoffmann, K. (2003).
    Vergleich zweier Messmethoden mit einem Goldstandard am Beispiel der 20-MHz-Sonographie und der klinischen Palpation zur Dickenbestimmung von pigmentierten Tumoren der Haut. Ultraschall in der Medizin, 24, 184-189.
  • Bissantz, N., Munk, A. (2002).
    A graphical selection method for parametric models in noisy inhomogeneous regression. Mon. Not. R. Astron. Soc., 336, 131-138.
  • Bissantz, N., Munk, A. (2002).
    New goodness of fit techniques in noisy inhomogeneous regression problems. With an application to the problem of recovering of the luminosity density of the Milky Way from surface brightness data. "Statistical Challenges in Modern Astronomy III" (eds. Feigelson, E.D., Babu, G.J.) Springer, New York..
  • Munk, A., Ruymgaart, F. (2002).
    Minimax rates for estimating the variance and its derivatives in nonparametric regression. Austr. New Zeal. Journ. Statist., 44, 479-488.
  • Derbort, S., Dette, H., Munk, A. (2002).
    Testing the additivity of regression curves. The Annals of the Inst. of Statist. Math., 54, 60-82.
  • Munk, A. (2002).
    Testing the goodness of fit of parametric regression models with random Toeplitz forms. Scand. Journ. Statist., 29 (3), 501-535.
  • Bissantz, N., Munk, A. (2001).
    New statistical goodness of fit techniques in noisy inhomogeneous inverse problems. With application to the recovering of the luminosity distribution of the Milky Way. Astron. & Astroph., 376, 735-744.
  • Bissantz, N., Munk, A. (2001).
    New Statistical Goodness of Fit Techniques Applied to the Recovery of the Milky Way Near-IR Luminosity Density Distribution - the 'Wild Bootstrap' Approach. "Galaxy Disks and Disk Galaxies" (eds. Funes S.J., J.G., Corsini, E.M.) ASP Conf. Ser., 230, 51-52.
  • Munk, A. (2001).
    On a problem in pharmaceutical statistics and the iteration of a peculiar nonlinear operator in the upper complex halfplane. Nonlinear Analysis, 47, 1513-1523.
  • Dette, H., Munk, A., Wagner, T. (2000).
    Testing model assumptions in multivariate regression. Journ. Nonpar. Statist., 12, 309-342.
  • Munk, A. (2000).
    Discussion of „Contributions of empirical and quantile processes to the asymptotic theory of goodness-of-fit tests“ by E. del Barrio, J.A. Cuesta-Albertos and C. Matran. Test, 9, 84-88.
  • Munk, A., Brown, L.D., Hwang, J.T.G. (2000).
    The bioequivalence problem – finding a compromise between theory and practice. Biom. Journ., 42, 1-21.
  • Czado, C., Munk, A. (2000).
    Noncanonical links in generalized linear models - when is the effort justified? Journ. Statist. Plann. Infer., 87, 317-345.
  • Munk, A. (2000).
    An unbiased test for the bioequivalence problem – the small sample case. Journ. Statist. Plann. Infer., 87, 69-86.
  • Munk, A. (2000).
    Connections between average and individual bioequivalence. Stat. in Medicine, 19, 2843-2854.
  • Munk, A. (1999).
    Conditional inference for the von Mises distribution with applications to Efron’s parabola model. Metrika, 50, 1-17.
  • Munk, A., Pflüger, R. (1999).
    1-alpha confidence rules are alpha/2 – level tests for convex hypothesis – with applications to the multivariate assessment of bioequivalence. Journ. Amer. Statist. Assoc., 94, 1311-1320.
  • Munk, A. (1999).
    A note on unbiased testing in equivalence assessment – another christmas tree. Statist. & Prob. Letters, 41, 401-406.
  • Munk, A., Dette, H. (1998).
    Nonparametric comparison of several regression functions: exact and asymptotic theory. Ann. Statist., 26, 2339-2369.
  • Dette, H, Munk, A. (1998).
    Validation of linear regression models. The Annals of Statistics, 26, 778-800.
  • Dette, H, Munk, A. (1998).
    A simple goodness of fit test for linear models under a random design assumption. Annals of the Inst. of Statist. Mathem., 50, 253-275.
  • Munk, a., Czado, C. (1998).
    Nonparametric validation of similar distributions and the assessment of goodness to fit. Journ. Roy. Statist. Soc. Ser. B, 60, 223-241.
  • Dette, H., Munk, A. (1998).
    Testing heteroscedasticity in nonparametric regression. Journ. Roy. Statist. Soc. Ser. B, 60, 693-708.
  • Dette, H., Munk, A., Wagner, T. (1998).
    Estimating the variance in nonparametric regression by quadratic forms – what is a reasonable choice? Journ. Roy. Statist. Soc. Ser. B, 60, 751-764.
  • Czado, C., Munk, A. (1998).
    Assessing the similarity of distributions – finite sample performance of the empirical Mallows distance. Journ. Computat. Simulat., 60, 319-346.
  • Munk, A. (1998).
    Cebysev experiments. Statistics, 31, 289-324.
  • Dette, H., Munk, A., Wagner, T. (1998).
    A review of variance estimators with extensions to multivariate nonparametric regression models. Multivariate Design and Sampling (ed. S. Gosh), Dekker, NY., 469-499.
  • Brown, L.D., Hwang, J.T.G., Munk, A. (1998).
    An unbiased test for the bioequivalence problem. The Annals of Statistics, 25, 2345-67.
  • Dette, H., Munk, A. (1997).
    Optimal allocations of treatments in equivalence assessment. Biometrics, 53, 1143-1150.
  • Brunner, E., Dette, H., Munk, A. (1997).
    Box-type approximations in heteroskedastic factorial designs. Journ. Americ. Statist. Assoc., 92, 1494-1503.
  • Nida-Rümelin, J., Schmidt, T., Munk, A. (1996).
    Iteration of independent decisions. Theory and Decision, 41, 257-280.
  • Munk, A. (1996).
    Equivalence and interval testing for Lehmann’s alternative. Journ. Americ. Stat. Assoc., 91, 1187-1197.
  • Dette, H., Munk, A. (1995).
    Sign regularity of a generalized Cauchy-kernel with applications. Journ. Statist. Plann. Inf., 52, 131-142.
  • Danneberg, O., Dette, H., Munk, A. (1994).
    An extension of Welch’s approximative t-solution to comparative bioequivalence trials. Biometrika, 81, 91-101.
  • Munk, A. (1994).
    On a method of combining double t-test and Anderson-Hauck test. Reader reaction response. Biometrics, 50, 885-886.
  • Munk, A. (1993).
    An improvement on commonly used tests in bioequivalence assessment. Biometrics, 49, 1225-31.

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