Research interests

Statistics for regression and stochastic process models (asymptotic efficiency), nonparametric and semiparametric inference, stochastic resonance, multivariate analysis

[Most articles are listed in MathSciNet]

[25]   U.U. Müller (2009). Estimating linear functionals in nonlinear regression with responses missing at random. Ann. Statist., 37, 2245-2277
33 pp.   .pdf  

[24]   U.U. Müller, A. Schick and W. Wefelmeyer (2009). Estimating the error distribution function in nonparametric regression with multivariate covariates. Statist. Probab. Lett. 79, 957-964.
11 pp.   .pdf

[23]  U.U. Müller, A. Schick and W. Wefelmeyer (2009). Estimating the innovation distribution in nonparametric autoregression. Probab. Theory Related Fields, 144, 53-77.
25 pp.    .pdf

[22]  U.U. Müller, A. Schick and W. Wefelmeyer (2009). Estimators for alternating nonlinear autoregression. J. Multivariate Anal., 100, 266-277.
19 pp.    .pdf

[21]  U.U. Müller, A. Schick and W. Wefelmeyer (2008). Estimators for partially observed Markov chains. Statistical Models and Methods for Biomedical and Technical Systems (F. Vonta, M. Nikulin, N. Limnios and C. Huber, eds.), Birkhäuser, Boston, 423-438.
15 pp.   .pdf

[20]  U.U. Müller, A. Schick and W. Wefelmeyer (2008). Optimality of estimators for misspecified semi-Markov models. Stochastics, 80, 2, 181-196.
13 pp.    .pdf

[19]  U.U. Müller, A. Schick and W. Wefelmeyer (2007). Estimating the error distribution function in semiparametric regression. Statist. Decisions, 25, 1, 1-18.
18 pp.    .pdf

[18]  U.U. Müller (2007). Weighted least squares estimators in possibly misspecified nonlinear regression. Metrika, 66, 1, 39-59.
22 pp.    .pdf

[17]  U.U. Müller, A. Schick and W. Wefelmeyer (2006). Efficient prediction for linear and nonlinear autoregressive models. Ann. Statist., 34, 5, 2496-2533.
38 pp.    .pdf

[16]  U.U. Müller, A. Schick and W. Wefelmeyer (2006). Imputing responses that are not missing. Probability, Statistics and Modelling in Public Health, Symposium in Honor of Marvin Zelen (M. Nikulin, D. Commenges and C. Huber, eds.), 350-363, Springer.
14 pp.    .pdf

[15]  U.U. Müller, A. Schick and W. Wefelmeyer (2005). Weighted residual-based density estimators for nonlinear autoregressive models. Statist. Sinica, 15, 177-195.
20 pp.    .pdf

[14]  P.E. Greenwood, U.U. Müller and L.M. Ward (2004). Soft threshold stochastic resonance. Phys. Rev. E, 70, 051110.
20 pp.    .pdf

[13]  P.E. Greenwood, U.U. Müller and W. Wefelmeyer (2004). An introduction to efficient estimation for semiparametric time series. Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life (M. S. Nikulin, N. Balakrishnan, M. Mesbah and N. Limnios, eds.), 253-272, Statistics for Industry and Technology, Birkhäuser, Basel.
16 pp.    .pdf

[12]  U.U. Müller, A. Schick and W. Wefelmeyer (2004). Estimating functionals of the error distribution in parametric and nonparametric regression. J. Nonparametr. Stat. 16, 525-548.
25 pp.    .pdf

[11]  P.E. Greenwood, U.U. Müller and W. Wefelmeyer (2004). Efficient estimation for semiparametric semi-Markov processes. In: Semi-Markov Processes and Their Applications (N. Limnios, ed.), Comm. Statist. Theory Meth., 33, 419-435.
17 pp.    .pdf

[10]  U.U. Müller, A. Schick and W. Wefelmeyer (2004). Estimating linear functionals of the error distribution in nonparametric regression. J. Statist. Plann. Inference, 119, 75-93.
20 pp.    .pdf

[9]  U.U. Müller, A. Schick and W. Wefelmeyer (2003). Estimating the error variance in nonparametric regression by a covariate-matched U-statistic. Statistics, 37, 3, 179-188.
11 pp.    .pdf

[8]  U.U. Müller and G. Osius (2003). Asymptotic normality of goodness-of-fit statistics for sparse Poisson data. Statistics, 37, 2,  119-143.
27 pp.    .pdf

[7]  P.E. Greenwood, U.U. Müller, L.M. Ward and W. Wefelmeyer (2003). Statistical analysis of stochastic resonance in a thresholded detector. Austrian J. Stat., 32, 1 & 2, 49 - 70.
22 pp.    .pdf

[6]  U.U. Müller and W. Wefelmeyer (2002). Autoregression, estimating functions, and optimality criteria. In: Advances in Statistics, Combinatorics and Related Areas (C. Gulati, Y.-X. Lin, J. Rayner and S. Mishra, eds.), 180-195, World Scientific Publishing, Singapore.
16 pp.    .pdf

[5]  U.U. Müller and W. Wefelmeyer (2002).  Estimators for models with constraints involving unknown parameters. Math. Meth. Stat., 11, 2,  221-235.
17 pp.    .pdf

[4]  U.U. Müller, A. Schick and W. Wefelmeyer (2001). Plug-in estimators in semiparametric stochastic process models. In: Selected Proceedings of the Symposium on Inference for Stochastic Processes (I. V. Basawa, C. C. Heyde and R. L. Taylor, eds.), 217-238, IMS Lecture Notes-Monograph Series, 37, Institute of Mathematical Statistics,  Beachwood, Ohio.
22 pp.    .pdf

[3]  U.U. Müller, A. Schick and W. Wefelmeyer (2001). Improved estimators for constrained Markov chain models. Statist. Probab. Lett., 54, 4, 427-435.
9 pp.    .pdf

[2]  U.U. Müller (2000). Nonparametric regression for threshold data. Can. J. Stat., 28, 2, 301-310.
12 pp.    .pdf

[1]  U.U. Müller and L.M. Ward (2000). Stochastic resonance in a statistical model of a time-integrating detector. Phys. Rev. E, 61, 4, 4286-4294.
9 pp.    .pdf

Accepted papers

U.U. Müller and W. Wefelmeyer. Estimation in nonparametric regression with nonregular errors. To appear in: Comm. Statist. Theory Methods (special issue in honor of M. Akahira).
13 pp.   .pdf   (Mar 2008)

U. Müller (1997). Asymptotic Normality of Goodness-of-Fit Statistics for Sparse Poisson and Case-Control Data. Ph.D. thesis, Universität Bremen.
150 pp.    .pdf.

U. Müller (1993). Experimente zum Auffinden relevanter Einflussfaktoren. Diploma thesis, Freie Universität Berlin, 74 pp.

Other papers and reports (not refereed)

U.U. Müller, A. Schick and W. Wefelmeyer (2007). Inference for alternating time series. In: Recent Advances in Stochastic Modeling and Data Analysis (C.H. Skiadas, ed.), 589-596, World Scientific, Singapore.
8 pp.    .pdf

U.U. Müller, A. Schick and W. Wefelmeyer (2004). Estimating the error distribution function in nonparametric regression. Technical report.
20 pp.    .pdf

U.U. Müller (2000). Goodness-of-fit statistics for large numbers of cells. In: Second International Conference on Mathematical Models in Reliability, Bordeaux, Universite Victor Sengalen, Bordeaux, France, July 4-7, 2000. Abstracts Book, Vol. 2, pp. 792-795.

U.U. Müller (1999). Nonparametric regression for threshold data. Universität Bremen, Mathematik-Arbeitspapiere A, 52.
18 pp.     .pdf   

U. Müller and G. Osius (1998). Asymptotic normality of goodness-of-fit statistics for sparse Poisson data. Universität Bremen, Mathematik-Arbeitspapiere A, 51,
15 pp.