Wolfgang Wefelmeyer

Articles

Preprint versions (pdf) of some of the following publications can be downloaded.

2023

[105] A. Schick and W. Wefelmeyer.
Efficient density estimation in an AR(1) model.
Electron. J. Stat. 17 (2023) 2880-2911.
32 pages     pdf     doi     MR4666304

2017

[104] W. Lee, P. E. Greenwood, N. Heckman and W. Wefelmeyer.
Preaveraged kernel estimators for the drift function of a diffusion process
in the presence of microstructure noise.
Stat. Inference Stoch. Process. 20 (2017) 237-252.
16 pages     pdf     doi     MR3656585

2016

[103] U. U. Müller, A. Schick and W. Wefelmeyer.
Density estimators for the convolution of discrete and continuous random variables.
Ann. I.S.U.P. 60 (2016) 55-65.
11 pages     pdf     MR3676309

2015

[102] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimators in step regression models.
Statist. Probab. Lett. 100 (2015) 124-129.
6 pages     pdf     doi     MR3324083

2014

[101] U. U. Müller and W. Wefelmeyer.
Estimating a density under pointwise constraints on the derivatives.
Math. Meth. Statist. 23 (2014) 201-209.
9 pages     pdf     doi     MR3266832

[100] U. U. Müller, A. Schick and W. Wefelmeyer.
Testing for additivity in partially linear regression
with possibly missing responses.
J. Multivariate Anal. 128 (2014) 51-61.
11 pages     pdf     doi     MR3199827

[99] U. U. Müller, A. Schick and W. Wefelmeyer.
Efficient estimators for alternating quasi-likelihood models.
J. Indian Statist. Assoc. 52 (2014) 1-17.
17 pages     pdf     MR3236325

2013

[98] A. Schick and W. Wefelmeyer.
Uniform convergence of convolution estimators
for the response density in nonparametric regression.
Bernoulli 19 (2013) 2250-2276.
27 pages     pdf     doi     MR3160553

[97] U. U. Müller, A. Schick and W. Wefelmeyer.
Non-standard behavior of density estimators
for functions of independent observations.
In: Stochastic Modeling Techniques and Data Analysis. International Conference,
Comm. Statist. Theory Methods 42 (2013) 2291-2300.
10 pages     pdf     doi     MR3170913

[96] U. U. Müller, A. Schick and W. Wefelmeyer.
Variance bounds for estimators in autoregressive models with constraints.
Statistics 47 (2013) 477-493.
17 pages     pdf     doi     MR3060924

2012

[95] A. Schick and W. Wefelmeyer.
Convergence in weighted L_1-norms of convolution estimators
for the response density in nonparametric regression.
J. Indian Statist. Assoc. 50 (2012) 241-261.
21 pages     pdf     MR2986288

[94] A. Schick and W. Wefelmeyer.
On efficient estimation of densities for sums of squared observations.
Statist. Probab. Lett. 82 (2012) 1637-1640.
4 pages     pdf     doi     MR2950998

[93] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating the error distribution function
in semiparametric additive regression models.
J. Statist. Plann. Inference 142 (2012) 552-566.
15 pages     pdf     doi     MR2843057

2011

[92] P. E. Greenwood, K. Küsters and W. Wefelmeyer.
The behavior of estimators in misspecified regression models.
In: Proceedings ASMDA 2011
(G. D'Amico, G. Di Biase, J. Janssen and R Manca, eds.), 576-583,
Università di Roma Sapienza 2011.
8 pages     pdf

[91] U. U. Müller, A. Schick and W. Wefelmeyer.
Optimal plug-in estimators for multivariate distributions
with conditionally independent components.
J. Nonparametr. Statist. 23 (2011) 1031-1050.
20 pages     pdf     doi     MR2854253

[90] A. Schick, Y. Wang and W. Wefelmeyer.
Tests for normality based on density estimators of convolutions.
Statist. Probab. Lett. 81 (2011) 337-343.
7 pages     pdf     doi     MR2764302

[89] P. E. Greenwood, A. Schick and W. Wefelmeyer.
Estimating the inter-arrival time density of Markov renewal processes
under structural assumptions on the transition distribution.
Statist. Probab. Lett. 81 (2011) 277-282.
6 pages     pdf     doi    MR2764294

2010

[88] U. U. Müller and W. Wefelmeyer.
Estimation in nonparametric regression with nonregular errors.
In: Recent Advances in Statistical Inference.
In Honor of Masafumi Akahira (M. Aoshima, ed.),
Comm. Statist. Theory Methods 39 (2010) 1619-1629.
11 pages     pdf     doi

2009

[87] A. Schick and W. Wefelmeyer.
Non-standard behavior of density estimators for sums of squared observations.
Statist. Decisions 27 (2009) 55-73.
19 pages     pdf     doi     MR2597426

[86] A. Schick and W. Wefelmeyer.
Improved density estimators for invertible linear processes.
In: Recent Advances in Theory and Applications of Statistics.
Festschrift for Shelemyahu Zacks (N. Mukhopadhyay, ed.),
Comm. Statist. Theory Methods 38 (2009) 3123-3147.
25 pages     pdf     doi     MR2568208

[85] A. Schick and W. Wefelmeyer.
Plug-in estimators for higher-order transition densities in autoregression.
ESAIM Probab. Statist. 13 (2009) 135-151.
17 pages     pdf     doi     MR2502027

[84] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating the error distribution function in nonparametric regression
with multivariate covariates.
Statist. Probab. Lett. 79 (2009) 957-964.
8 pages     pdf     doi     MR2509488

[83] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating the innovation distribution in nonparametric autoregression.
Probab. Theory Related Fields 144 (2009) 53-77.
25 pages     pdf     doi     MR2480785

[82] A. Schick and W. Wefelmeyer.
Convergence rates of density estimators for sums of powers of observations.
Metrika 69 (2009) 249-264.
16 pages     pdf     doi     MR2481923

[81] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimators for alternating nonlinear autoregression.
J. Multivariate Anal. 100 (2009) 266-277.
12 pages     pdf     doi     MR2474773

2008

[80] A. Schick and W. Wefelmeyer.
Some developments in semiparametric statistics.
In: Special Issue on Semiparametric Methods (B. Kedem, ed.),
J. Stat. Theory Pract. 2 (2008) 475-491.
17 pages     pdf     doi     MR2528794

[79] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimators for partially observed Markov chains.
In: Statistical Models and Methods for Biomedical and Technical Systems
(F. Vonta, M. Nikulin, N. Limnios and C. Huber-Carol, eds.), 419-433,
Birkhäuser, Boston 2008.
15 pages     pdf     doi     MR2462769

[78] A. Schick and W. Wefelmeyer.
Root-n consistency in weighted L_1-spaces for density estimators
of invertible linear processes.
Stat. Inference Stoch. Process. 11 (2008) 281-310.
30 pages     pdf     doi     MR2438498

[77] A. Schick and W. Wefelmeyer.
Convergence rates in weighted L_1 spaces of kernel density estimators
for linear processes.
ALEA 4 (2008) 117-129.
13 pages     pdf     online     MR2413090

[76] U. U. Müller, A. Schick and W. Wefelmeyer.
Optimality of estimators for misspecified semi-Markov models.
In: Festschrift for Priscilla Greenwood (N. Bingham and I. Evstigneev, eds.),
Stochastics 80 (2008) 181-196.
16 pages     pdf     arxiv     doi     MR2402163

[75] A. Schick and W. Wefelmeyer.
Prediction in moving average processes.
J. Statist. Plann. Inference 138 (2008) 694-707.
14 pages     pdf     doi     MR2382883

2007

[74] U. U. Müller, A. Schick and W. Wefelmeyer.
Inference for alternating time series.
In: Recent Advances in Stochastic Modeling and Data Analysis
(C. H. Skiadas, ed.), 589-596,
World Scientific, Singapore 2007.
8 pages     pdf     MR2449742

[73] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating the error distribution function in semiparametric regression.
Statist. Decisions 25 (2007) 1-18.
18 pages     pdf     doi     MR2370101

[72] A. Schick and W. Wefelmeyer.
Uniformly root-n consistent density estimators
for weakly dependent invertible linear processes.
Ann. Statist. 35 (2007) 815-843.
29 pages     pdf     arxiv     doi     MR2336870

[71] A. Schick and W. Wefelmeyer.
Prediction in invertible linear processes.
Silver Jubilee Issue Dedicated to Richard A. Johnson
(H. L. Koul, M. Akritas and A. Schick, eds.),
Statist. Probab. Lett. 77 (2007) 1322-1331.
10 pages     pdf     doi     MR2392802

[70] A. Schick and W. Wefelmeyer.
Root-n consistent density estimators of convolutions in weighted L_1-norms.
J. Statist. Plann. Inference 137 (2007) 1765-1774.
10 pages     pdf     doi     MR2323861

2006

[69] U. U. Müller, A. Schick and W. Wefelmeyer.
Efficient prediction for linear and nonlinear autoregressive models.
Ann. Statist. 34 (2006) 2496-2533.
38 pages     pdf     arxiv     doi     MR2291508

[68] A. Schick and W. Wefelmeyer.
Pointwise convergence rates and central limit theorems
for kernel density estimators in linear processes.
Statist. Probab. Lett. 76 (2006) 1756-1760.
5 pages     pdf     doi     MR2274137

[67] A. Schick and W. Wefelmeyer.
Efficient estimators for time series.
In: Frontiers in Statistics. Dedicated to Peter Bickel
(J. Fan and H. L. Koul, eds.), 45-62,
Imperial College Press, London 2006.
18 pages     pdf     MR2325996

[66] U. U. Müller, A. Schick and W. Wefelmeyer.
Imputing responses that are not missing.
In: Probability, Statistics and Modelling in Public Health.
Dedicated to Marvin Zelen
(M. Nikulin, D. Commenges and C. Huber, eds.), 350-363,
Springer, New York 2006.
14 pages     pdf     MR2230741

2005

[65] U. U. Müller, A. Schick and W. Wefelmeyer.
Weighted residual-based density estimators
for nonlinear autoregressive models.
Statist. Sinica 15 (2005) 177-195.
19 pages     pdf     online     MR2125727

2004

[64] A. Schick and W. Wefelmeyer.
Functional convergence and optimality of plug-in estimators
for stationary densities of moving average processes.
Bernoulli 10 (2004) 889-917.
29 pages     pdf     doi     MR2093616

[63] A. Schick and W. Wefelmeyer.
Root n consistent density estimators for sums of independent random variables.
J. Nonparametr. Statist. 16 (2004) 925-935.
11 pages     pdf     doi     MR2094747

[62] P. E. Greenwood, U. U. Müller and W. Wefelmeyer.
An introduction to efficient estimation for semiparametric time series.
In: 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 2004.
20 pages     pdf     MR2091617

[61] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating functionals of the error distribution in parametric
and nonparametric regression.
J. Nonparametr. Statist. 16 (2004) 525-548.
24 pages     pdf     doi     MR2073040

[60] A. Schick and W. Wefelmeyer.
Estimating invariant laws of linear processes by U-statistics.
Ann. Statist. 32 (2004) 603-632.
30 pages     pdf     arxiv     jstor     doi     MR2060171

[59] P. E. Greenwood, U. U. Müller and W. Wefelmeyer.
Efficient estimation for semiparametric semi-Markov processes.
In: Semi-Markov Processes and Their Applications (N. Limnios, ed.),
Comm. Statist. Theory Methods 33 (2004) 419-435.
17 pages     pdf     doi     MR2056947

[58] A. Schick and W. Wefelmeyer.
Root $n$ consistent and optimal density estimators
for moving average processes.
Scand. J. Statist. 31 (2004) 63-78.
16 pages     pdf     doi     MR2042599

[57] S. Penev, H. Peng, A. Schick and W. Wefelmeyer.
Efficient estimators for functionals of Markov chains
with parametric marginals.
Statist. Probab. Lett. 66 (2004) 335-345.
11 pages     pdf     doi     MR2045478

[56] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating linear functionals of the error distribution
in nonparametric regression.
J. Statist. Plann. Inference 119 (2004) 75-93.
19 pages     pdf     doi     MR2018451

2003

[55] U. U. Müller, A. Schick and W. Wefelmeyer.
Estimating the error variance in nonparametric regression
by a covariate-matched U-statistic.
Statistics 37 (2003) 179-188.
10 pages     pdf     doi     MR1986175

[54] P. E. Greenwood, U. U. Müller, L. M. Ward and W. Wefelmeyer.
Statistical analysis of stochastic resonance in a threshold detector.
Austrian J. Statist. 32 (2003) 49-70.
22 pages     pdf     online

[53] P. E. Greenwood and W. Wefelmeyer.
Empirical estimators based on MCMC data.
In: Handbook of Statistics 21 (D. N. Shanbhag and C. R. Rao, eds.), 337-370,
Elsevier, Amsterdam 2003.
36 pages     pdf     MR1973548

2002

[52] A. Schick and W. Wefelmeyer.
Efficient estimation in invertible linear processes.
Math. Methods Statist. 11 (2002) 358-379.
22 pages     pdf     MR1964452

[51] U. U. Müller and W. Wefelmeyer.
Estimators for models with constraints involving unknown parameters.
Math. Methods Statist. 11 (2002) 221-235.
17 pages     pdf     MR1941317

[50] U. U. Müller and W. Wefelmeyer.
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, Singapore 2002.
16 pages     pdf     MR2063849

[49] A. Schick and W. Wefelmeyer.
Estimating the innovation distribution in nonlinear autoregressive models.
Ann. Inst. Statist. Math. 54 (2002) 245-260.
16 pages     pdf     doi     MR1910172

[48] A. Schick and W. Wefelmeyer.
Estimating joint distributions of Markov chains.
Stat. Inference Stoch. Process. 5 (2002) 1-22.
22 pages     pdf     doi     MR1881848

2001

[47] P. E. Greenwood, A. Schick and W. Wefelmeyer.
Comment on: Inference for semiparametric models:
some questions and an answer,
by Peter J. Bickel and Jaimyoung Kwon.
Statist. Sinica 11 (2001) 892-906.
15 pages     pdf     online     MR1867326

[46] U. U. Müller, A. Schick and W. Wefelmeyer.
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.), 213-234,
IMS Lecture Notes-Monograph Series 37,
Institute of Mathematical Statistics, Beachwood, Ohio 2001.
22 pages     pdf     MR2002512

[45] U. U. Müller, A. Schick and W. Wefelmeyer.
Improved estimators for constrained Markov chain models.
Statist. Probab. Lett. 54 (2001) 427-435.
9 pages     pdf     doi     MR1861389

[44] M. Kessler, A. Schick and W. Wefelmeyer.
The information in the marginal law of a Markov chain.
Bernoulli 7 (2001) 243-266.
24 pages     pdf     jstor     MR1828505

2000

[43] I. W. McKeague and W. Wefelmeyer.
Markov chain Monte Carlo and Rao-Blackwellization.
J. Statist. Plann. Inference 85 (2000) 171-182.
12 pages     pdf     doi     MR1759248

1999

[42] P. E. Greenwood and W. Wefelmeyer.
Characterizing efficient empirical estimators for local interaction Gibbs fields.
Stat. Inference Stoch. Process. 2 (1999) 119-134.
16 pages     pdf     doi     MR1918878

[41] A. Schick and W. Wefelmeyer.
Efficient estimation of invariant distributions
of some semiparametric Markov chain models.
Math. Meth. Statist. 8 (1999) 426-440.
15 pages     pdf     MR1735474

[40] P. E. Greenwood, L. M. Ward and W. Wefelmeyer.
Statistical analysis of stochastic resonance in a simple setting.
Phys. Rev. E 60, 4 (1999) 4687-4695.
9 pages     pdf     doi

[39] P. E. Greenwood, I. W. McKeague and W. Wefelmeyer.
Von Mises type statistics for single site updated local interaction random fields.
Statist. Sinica 9 (1999) 699-712.
14 pages     pdf     online     MR1711655

[38] W. Wefelmeyer.
Efficient estimation in Markov chain models: an introduction.
In: Asymptotics, Nonparametrics, and Time Series (S. Ghosh, ed.), 427-459,
Statistics: Textbooks and Monographs 158, Dekker, New York 1999.
33 pages     pdf     MR1724705

[37] P. E. Greenwood and W. Wefelmeyer.
Reversible Markov chains and optimality of symmetrized empirical estimators.
Bernoulli 5 (1999) 109-123.
15 pages     pdf     jstor     MR1673568

1998

[36] P. E. Greenwood, I. W. McKeague and W. Wefelmeyer.
Information bounds for Gibbs samplers.
Ann. Statist. 26 (1998) 2128-2156.
29 pages     pdf     jstor     doi     MR1700224

[35] W. Wefelmeyer.
Judging MCMC estimators by their asymptotic variance.
In: Prague Stochastics '98, Vol. II
(M. Husková, P. Lachout and J. A. Vísek, eds.), 591-596,
Union of Czech Mathematicians and Physicists, 1998.
6 pages     pdf

[34] P. E. Greenwood and W. Wefelmeyer.
Cox's factoring of regression model likelihoods for continuous time processes.
Bernoulli 4 (1998) 65-80.
16 pages     pdf     jstor     MR1611875

1997

[33] W. Wefelmeyer.
Quasi-likelihood regression models for Markov chains.
In: Selected Proceedings of the Symposium on Estimating Functions
(I. V. Basawa, V. P. Godambe and R. L. Taylor, eds.), 149-173,
IMS Lecture Notes-Monograph Series,
Institute of Mathematical Statistics, Hayward, California 1997.
25 pages     pdf     MR1837803

[32] P. E. Greenwood and W. Wefelmeyer.
Partial likelihood and estimating equations.
In: Selected Proceedings of the Symposium on Estimating Functions
(I. V. Basawa, V. P. Godambe and R. L. Taylor, eds.), 19-33,
IMS Lecture Notes-Monograph Series,
Institute of Mathematical Statistics, Hayward, California 1997.
15 pages     pdf     MR1837794

[31] P. E. Greenwood and W. Wefelmeyer.
Maximum likelihood estimator and Kullback-Leibler information
in misspecified Markov chain models.
Teor. Veroyatnost. i Primenen. 42 (1997) 169-178.
Theory Probab. Appl. 42 (1998) 103-111.
9 pages     pdf     MR1453336

[30] W. Wefelmeyer.
Adaptive estimators for parameters of the autoregression function
of a Markov chain.
J. Statist. Plann. Inference 58 (1997) 389-398.
10 pages     pdf     doi     MR1450023

1996

[29] P. E. Greenwood, I. W. McKeague and W. Wefelmeyer.
Outperforming the Gibbs sampler empirical estimator
for nearest neighbor random fields.
Ann. Statist. 24 (1996) 1433-1456.
24 pages     pdf     jstor     doi     MR1416641

[28] P. E. Greenwood and W. Wefelmeyer.
Empirical estimators for semi-Markov processes.
Math. Meth. Statist. 5 (1996) 299-315.
17 pages     pdf     MR1417674

[27] R. Dahlhaus and W. Wefelmeyer.
Asymptotically optimal estimation in misspecified time series models.
Ann. Statist. 24 (1996) 952-974.
23 pages     pdf     jstor     doi     MR1401832

[26] W. Wefelmeyer.
Quasi-likelihood models and optimal inference.
Ann. Statist. 24 (1996) 405-422.
18 pages     pdf     jstor     doi     MR1389898

1995

[25] P. E. Greenwood and W. Wefelmeyer.
Efficiency of empirical estimators for Markov chains.
Ann. Statist. 23 (1995) 132-143.
12 pages     jstor     doi     MR1331660

1994

[24] W. Wefelmeyer.
Improving maximum quasi-likelihood estimators.
In: Asymptotic Statistics (P. Mandl, M. Husková, eds.), 467-474,
Physika-Verlag, Heidelberg 1994.
8 pages     MR1311966

[23] W. Wefelmeyer.
An efficient estimator for the expectation of a bounded function
under the residual distribution of an autoregressive process.
Ann. Inst. Statist. Math. 46 (1994) 309-315.
7 pages     doi     MR1293166

[22] P. E. Greenwood and W. Wefelmeyer.
Optimality properties of empirical estimators for multivariate point processes.
J. Multivariate Anal. 49 (1994) 202-217.
16 pages     doi     MR1276435

[21] P. E. Greenwood and W. Wefelmeyer.
Nonparametric estimators for Markov step processes.
Stochastic Process. Appl. 52 (1994) 1-16.
16 pages     doi     MR1289165

1993

[20] W. Wefelmeyer.
Estimating functions and efficiency in a filtered model.
In: Frontiers in Pure and Applied Probability, Vol. 1
(H. Niemi, G. Högnäs, A. N. Shiryaev, A. V. Melnikov, eds.), 287-295,
VSP, Utrecht 1993.
9 pages

[19] P. E. Greenwood and W. Wefelmeyer.
Asymptotic minimax results for stochastic process families with critical points.
Stochastic Process. Appl. 44 (1993) 107-116.
10 pages     doi     MR1198665

1992

[18] P. E. Greenwood and W. Wefelmeyer.
Partially specified filtered models and efficiency.
Teor. Veroyatnost. i Primenen. 37 (1992) 162-165.
Theory Probab. Appl. 37 (1992) 139-142.
4 pages     MR1211221

1991

[17] W. Wefelmeyer.
Efficient estimation in multiplicative counting process models.
Statist. Decisions 9 (1991) 301-317.
17 pages     MR1149338

[16] W. Wefelmeyer.
A generalization of asymptotically linear estimators.
Statist. Probab. Lett. 11 (1991) 195-199.
5 pages     doi     MR1097974

[15] P. E. Greenwood and W. Wefelmeyer.
On optimal estimating functions for partially specified
counting process models.
In: Estimating Functions (V. P. Godambe, ed.), 147-160,
Oxford University Press 1991.
14 pages     MR1163999

[14] P. E. Greenwood and W. Wefelmeyer.
Efficient estimation in a nonlinear counting-process regression model.
Canad. J. Statist. 19 (1991) 165-178.
14 pages     jstor     MR1128404

[13] P. E. Greenwood and W. Wefelmeyer.
Efficient estimating equations for nonparametric filtered models.
In: Statistical Inference in Stochastic Processes
(N. U. Prabhu, I. V. Basawa, eds.), 107-141,
Marcel Dekker, New York 1991.
35 pages     MR1138260

1990

[12] P. E. Greenwood and W. Wefelmeyer.
Efficiency of estimators for partially specified filtered models.
Stochastic Process. Appl. 36 (1990) 353-370.
18 pages     doi     MR1084985

1988

[11] W. Wefelmeyer.
Local asymptotic normality with rates.
In: Probability Theory and Mathematical Statistics with Applications
(W. Grossmann, J. Mogyoródi, I. Vincze, W. Wertz, eds.), 439-447,
Reidel, Dordrecht 1988.
9 pages     MR0956718

1987

[10] W. Wefelmeyer.
Testing hypotheses on independent, not identically distributed models.
In: Mathematical Statistics and Probability Theory, Vol. A, Theoretical Aspects
(M. L. Puri, P. Révész, W. Wertz, eds.), 267-282,
Reidel, Dordrecht 1987.
16 pages     MR0922701

[9] W. Wefelmeyer.
Uniform approximation of log-likelihood ratios in the i.i.d. case.
Commun. Statist. - Theory Meth. 16 (1987) 1265-1280.
16 pages     doi     MR0896548

1986

[8] W. Droste and W. Wefelmeyer.
Asymptotic concentration of estimators and dispersivity.
Statist. Decisions 4 (1986) 75-84.
10 pages     MR0838877

1985

[7] W. Wefelmeyer.
Differentiability of likelihood ratios with rates.
Probab. Math. Statist. 6 (1985) 109-120.
12 pages     MR0866821

[6] W. Wefelmeyer.
A counterexample concerning monotone unimodality.
Statist. Probab. Lett. 3 (1985) 87-88.
2 pages     doi     MR0792795

[5] W. Droste and W. Wefelmeyer.
A note on strong unimodality and dispersivity.
J. Appl. Probab. 22 (1985) 235-239.
5 pages    jstor     MR0776904

1984

[4] W. Droste and W. Wefelmeyer.
On Hajek's convolution theorem.
Statist. Decisions 2 (1984) 131-144.
14 pages     MR0746129

1979

[3] J. Pfanzagl and W. Wefelmeyer.
Addendum to ``A third-order optimum property
of the maximum likelihood estimator''.
J. Multivariate Anal. 9 (1979) 179-182.
4 pages     doi     MR0530650

1978

[2] J. Pfanzagl and W. Wefelmeyer.
An asymptotically complete class of tests.
Z. Wahrscheinlichkeitstheorie verw. Gebiete 45 (1978) 49-72.
24 pages     doi     MR0507972

[1] J. Pfanzagl and W. Wefelmeyer.
A third-order optimum property of the maximum likelihood estimator.
J. Multivariate Anal. 8 (1978) 1-29.
29 pages     doi     MR0489252