Preprints and Working Papers:

• Holzmann, H., Meister, A. (2020)
  Rate-optimal nonparametric estimation for random coefficient regression models. [arXiv]. In revision at Bernoulli
• Werner, H., Holzmann, H., Vandekerkhove, P. (2020)
  Adaptive estimation in the supremum norm for nonparametric mixtures of regressions. Working paper, in revision at EJS.
• Albisetti, I., Balabdaoui, F., Holzmann, H. (2020)
  Testing for spherical and elliptical symmetry. Working paper, in revision at JMVA.
• Bibinger, M. (2019).
  Cusum tests for changes in the Hurst exponent and volatility of fractional Brownian motion. [arXiv]
• Proksch, K., Bissantz, N., Holzmann, H. (2019)
  Simultaneous inference for Berkson errors-in-variables regression under fixed design. Working paper.
• Zwingmann, T., Holzmann, H. (2016).
  Asymptotics for the expected shortfall. [arXiv]
  
  

2019

• Bengs, V., Holzmann, H. (2019)
  Adaptive confidence sets for kink estimation. Electronic J. Statistics, 13(1), 1523-1579. Link.
  
• Bengs, V., Eulert, M., Holzmann, H. (2019)
  Asymptotic confidence sets for the jump curve in bivariate regression problems. J. Multivariate Analysis, doi: 10.1016/j.jmva.2019.02.017. [arXiv]
• Becker, A.-K., Holzmann, H. (2019)
  Nonparametric identication in the dynamic stochastic block model. IEEE Transactions on Information Theory, doi:10.1109/TIT.2019.2893947. [arXiv]
• Bibinger, M., Madensoy, M. (2019).
  Change-point inference on volatility in noisy Itô semimartingales. Stochastic processes and their applications 129(12), pp. 4878-4925, doi:10.1016/j.spa.2018.12.013.  [arXiv]
• Bibinger, M., Neely, C., Winkelmann, L. (2019).
  Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book. Journal of Econometrics 209(2), pp. 158-184, doi: 10.1016/j.jeconom.2019.01.001 [preprint]
• Bibinger, M., Trabs, M. (2019).
  Volatility estimation for stochastic PDEs using high-frequency observations. Stochastic processes and their applications, doi: 10.1016/j.spa.2019.09.002 [arXiv]
• Bibinger, M., Trabs, M. (2019).
  On central limit theorems for power variations of the solution to the stochastic heat equation. In Stochastic Models, Statistics and Their Applications (Springer Proceedings in Mathematics & Statistics, PROMS, volume 294), pp. 69-84, Springer, Cham, doi: 10.1007/978-3-030-28665-1 [arXiv]
• Zwingmann, T., Holzmann, H. (2019)
  Weak convergence of quantile and expectile processes under general assumptions. [arXiv]. Bernoulli, to appear.

2018

• Bibinger, M., Winkelmann, L. (2018).
  Common price and volatility jumps in noisy high-frequency data. Electronic Journal of Statistics 12(1), pp. 2018-2073.  [arXiv]

2017

• Bibinger, M., Jirak, M., Vetter, M. (2017)
  Nonparametric change-point analysis of volatility. The Annals of Statistics 45(4), pp. 1542-1578. [arXiv]
• Bibinger, M., Hautsch, N., Malec, P., Reiß, M. (2017).
  Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence. Journal of Business and Economic Statistics, to appear, [SSRN]
• Holzmann, H., Klar, B. (2017).
  Discussion of ``Elicitability and backtesting: Perspectives for banking regulation''. Invited discussion, Annals of Applied Statistics 11, 1875-1882. Preprint.
• Holzmann, H., Klar, B. (2017).
  Focusing on regions of interest in forecast evaluation. Annals of Applied Statistics 11, 2404-2431, doi: 10.1214/17-AOAS1088 [pdf]
  Former version including hypothesis testing: Weighted scoring rules and hypothesis testing. Preprint.
• Hoderlein, H.,  Holzmann, H., Meister, A. (2017).
  The triangular model with random coefficients. Journal of Econometrics  216, 144-169, doi: 10.1016/j.jeconom.2017.05.018 [pdf], [ supplement]
• Hoderlein, S., Holzmann, H., Kasy, M., Meister, A. (2017)
  Correction note to "Instrumental variables with unrestricted heterogeneity and continuous treatment". Review of Economic Studies 84, 964–968, doi: 10.1093/restud/rdw027. [pdf]
• Vetter, M., Zwingmann, T. (2017)
  A note on central limit theorems for quadratic variation in case of endogenous observation times. Electronic Journal of Statistics, 11(1), pp. 963-980. [arXiv]

2016

• Holzmann, H., Klar, B. (2016)
  Expectile Asymptotics. Electronic Journal of Statistics 11, 2355-2371. [arXiv]
• Alexandrovich, G., Holzmann, H., Leister, A. (2016)
  Nonparametric identification and maximum likelihood estimation of hidden Markov models. Biometrika 103, 423–434. [arXiv]
• Hohmann, D.,  Holzmann, H. (2016).
  Weighted angle Radon transform: Convergence rates and efficient estimation. Statistica Sinica 26, 157-175. [pdf]
• Bibinger, M., Jirak, M., Reiß, M. (2016)
  Volatility estimation under one-sided errors with applications to limit order books. The Annals of Applied Probability 26(5), pp. 2754-2790. 
• Bibinger, M., Mykland, P. A. (2016)
  Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing. Scandinavian Journal of Statistics 43(4), pp. 1078-1102. 
• Bibinger, M. (2016) Book review on Michael Evans `Measuring statistical evidence using relative belief' (Chapman & Hall/CRC Press, Boca Raton, FL, 2015). Journal of the American Statistical Association 111(514), pp. 916–917.

2015

• Chernozhukov, V.,  Fernández-Vál, I., Hoderlein, S., Holzmann, H., Newey, W. (2015).
  Nonparametric Identification in Panels using Quantiles. Journal of Econometrics 188, 378–392. Preprint
  
• Holzmann, H.,  Schwaiger, F. (2015).
  Hidden Markov Models with state-dependent mixtures: Minimal representation, model testing and applications to clustering. Statistics and Computing 25, 1185-1200 [ preprint] , supplement.

2014

• Alexandrovich, G. (2014) 
  A Note on the Article 'Inference for multivariate normal mixtures' by J. Chen and X. Tan. J. Multivariate Analysis   129, 245 – 248.  [preprint]
• Alexandrovich, G. (2014) 
  Penalized Maximum Likelihood Estimation for Gaussian hidden Markov Models.   pdf.
• Alexandrovich, G. (2014) 
  An exact Newton's method for ML estimation of a Gaussian mixture.  pdf.
• Holzmann, H.,  Schwaiger, F. (2014).
  Testing for the number of states in hidden Markov models. to appear: Computational Statistics and Data Analysis.
  
• Bissantz, N.,  Holzmann, H.,  Proksch, K. (2014).
  Confidence regions for images observed under the Radon transform. J. Multivariate Analysis 128, 86–107. [preprint]
  
• Holzmann, H., Eulert, M. (2014).
  The role of the information set for forecasting - with applications to risk management. Annals of Applied Statistics 8, 595-621. [preprint]
• Dannemann, J., Holzmann, H., Leister, A. (2014).
  Semiparametric hidden Markov models: Identifiability and estimation. WIREs Comp Stat, 6: 418-425. doi:10.1002/wics.1326 [ Preprint]

2013

• Vollmer, S., Holzmann, H., Ketterer, F., Klasen, S., Canning, D. (2013).
  The Emergence of Three Human Development Clubs. PLOS One 8,  doi:10.1371/journal.pone.0057624 [ Preprint]
• Alexandrovich, G., Holzmann, H. (2013).
  Discussion of "How to find an appropriate clustering for mixed type variables with application to socio-economic stratification" by C. Hennig and Liao. J. Royal Statist. Soc. Ser. C 63, 32-33.
  
• Hohmann, D., Holzmann, H. (2013).
  Semiparametric location mixtures with distinct components. Statistics 47 348-362, published online 31 Jan 2012, DOI 10.1080/02331888.2011.652118.
• Hohmann, D., Holzmann, H. (2013).
  Two-component mixtures with independent coordinates as conditional mixtures: Nonparametric identification and estimation. Electron. J. Statist. 7 859-880, DOI 10.1214/13-EJS792. [ pdf] [ Technical Report]
• Vollmer, S.,  Holzmann, H., Ketterer, F.,  Klasen, S. (2013).
  Distribution dynamics of Regional GDP per Employee in Unified Germany. Empirical Economics 44, 491-509, DOI: 10.1007/s00181-011-0543-3.
• Vollmer, S., Holzmann, H.,  Schwaiger, F. (2013). 
  Peaks vs. Components. Review of Development Economics 17, 352–364. [ Preprint]
• Alexandrovich, G., Holzmann, H., Ray, S. (2013).
  On the number of modes of finite mixtures of elliptical distributions. Algorithms from and for Nature and Life: Studies in Classification, Data Analysis, and Knowledge Organization 49-57. [ Preprint]
• Holzmann, H., Leister, A. (2013).
  Discussion of "Large covariance estimation by thresholding principal orthogonal complements" by J. Fan, Y. Liao and M. Mincheva. J. R. Statist. Soc.B  75, part 4. [ Supplement]
  

2012

• Ketterer, F., Holzmann, H. (2012).
  Testing for intercept-scale switch in linear autoregression. Canadian J. Statist. 44, 427-446. [ Preprint]
• Holzmann, H., Ketterer, F. (2012).
  Feasible Tests for regime switching in autoregressive models. Working Paper, Marburg University. [ pdf]
  

2011

• Böhringer, S., Holzmann, H. (2011).
  Evaluating HWE and Association in Genome Wide Association Studies: A Unified Procedure. Working paper, Marburg University. [ Preprint]

2010

• Balabdaoui, F., Bissantz, K., Bissantz, N., Holzmann, H. (2010).
  Demonstrating single- and multiple-SecYEG pore ionic transmembrane currents: Statistical testing for the number of modes of noisy observations. J. American Statist. Assoc., 105, 136-146 [ Preprint]
  
• Birke, M., Bissantz, N., Holzmann, H. (2010).
  Confidence bands for inverse regression models. Inverse Problems, 26, doi: 10.1088/0266-5611/26/11/115020 [ Preprint]
• Bissantz, N., Holzmann, H., Pawlak, M. (2010).
  Improving PSF calibration in confocal microscopic imaging - estimating and exploiting bilateral symmetry. Annals of Applied Statistics, 4, 1871-1891 [ Preprint]
• Dannemann, J., Holzmann, H. (2010).
  Testing for two components in a switching regression model. Comput. Statist. Data Anal., 64 (6), 1592-1604 [ Preprint]
  
• Hoderlein, S., Holzmann, H. (2010).
  Demand Analysis as an Ill-Posed Inverse Problem with Semiparametric Specification. Econometric Theory, Available on CJO 04 Nov 2010 doi:10.1017/S0266466610000423 [ Preprint]
• Min, A., Holzmann, H., Czado, C. (2010).
  Model selection strategies for identifying most relevant covariates in homoscedastic linear models. Comput. Statist. Data Anal., 54, 3194-3211 [ Preprint]
  

2009

• Bissantz N., Holzmann H., Pawlak M. (2009).
  Testing for Image Symmetries -- with Application to Confocal Microscopy. IEEE Transactions on Information Theory, 55, 1841-1855 [ 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]

2008

• Bissantz, N., Holzmann, H. (2008).
  Statistical inference for inverse problems. Inverse Problems, 24, doi: 10.1088/0266-5611/24/3/034009 [ Preprint]
  
• Dannemann, J., Holzmann, H. (2008).
  Testing for two states in a hidden Markov model. Canad. J. Statist., 36 (4), 505-520 [ Preprint]
• Dannemann, J., Holzmann, H. (2008).
  Likelihood ratio testing for hidden Markov models under nonstandard conditions. Scand. J. Statist., 35 (2), 309-321 [ Preprint]
• Dannemann, J., Holzmann, H. (2008).
  The likelihood ratio test for hidden Markov models in two-sample problems. Comput. Statist. Data Anal., 52, 1850-1859 [ Preprint]
• Denker, M., Holzmann, H. (2008).
  Markov partitions for fibre expanding systems. COLLOQUIUM MATHEMATICUM, 110, 485-492 [ Preprint]
• Holzmann, H., Munk, A. (2008).
  Reply to Reader Reacton: On the nonidentifiability of population sizes. Biometrics, 64, 979-981 [ Preprint]
  
• Holzmann, H., Vollmer, S. (2008).
  A likelihood ratio test for bimodality in two-component mixtures -- with application to regional income distribution in the EU. AStA - Advances in Statistical Analysis, 92, 57-69 [ Preprint]
• Holzmann, H. (2008).
  Testing parametric models in the presence of instrumental variables. Statist. Prob. Letters, 78, 629-636 [ Preprint]

2007

• 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 [ Preprint]
• Bissantz, N., Holzmann, H. (2007).
  Estimation of a quadratic regression functional using the sinc kernel. J. Statist. Plann. Inference, 137, 712-719 [ Preprint]
• Holzmann, H., Bissantz, N. und Munk, A. (2007).
  Density testing in a contaminated sample. J. Multivariate Analysis, 98, 57-75 [ Preprint]

2006

• 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: Supporting Material--Proofs. Biometrics, 62, supporting material. [ Preprint]
• Holzmann, H., Boysen, L. (2006).
  Integrated square error asymptotics for supersmooth deconvolution. Scand. J. Statist., 33, 849-860 [ Preprint]
• Holzmann, H., Munk, A., Gneiting, T. (2006).
  Identifiability of finite mixtures of elliptical distributions. Scand. J. Statist., 33, 753-764 [ Preprint]
• Holzmann, H., Munk, A., Zucchini, W. (2006).
  On identifiability in capture-recapture models. Biometrics, 62, 934-936 [ Preprint]
• 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]

2005

• 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]
• Holzmann, H. (2005).
  The central limit theorem for stationary Markov processes with normal generator -- with applications to hypergroups. Stochastics, 77, 371-380 [ Preprint]
• Holzmann, H. (2005).
  Martingale approximations for continuous-time and discrete-time stationary Markov processes. Stochastic Processes and Their Applications, 115, 1518-1529 [ Preprint]

2004

• Gordin, M., Holzmann, H. (2004).
  The central limit theorem for stationary Markov chains under invariant splittings. Stochastics and Dynamics, 4, 15-30 [ Preprint]
• Holzmann, H., Koch, S., Min, A. (2004).
  An Almost Sure Limit Theorem for U-Statistics. Statistics and Probability Letters, 69, 261-269 [ Preprint]
• Holzmann, H., Munk, A., Stratmann, B. (2004).
  Identifiability of finite mixtures - with applications to circular distributions. Sankhya, 66, 440-450 [ Preprint]