Publikationen in referierten Zeitschriften
- Doukhan, P., Mamode Khan, N., and Neumann, M. H.
Mixing properties of integer-valued GARCH processes.
Latin American Journal of Probability and Statistics 18, 1--20, (2021). - Neumann, M. H.
Bootstrap for integer-valued generalized GARCH(p,q) processes.pdf, 507 kb
Statistica Neerlandica, published online 19 February 2021. (2021). - Fokianos, K., Leucht, A., and Neumann, M. H.
On integrated L1 convergence rate of an isotonic regression estimator for multivariate observations.
IEEE Transactions on Information Theory 66 (10). 6389--6402. (2020). - Geller, J. and Neumann, M. H.
Improved local polynomial estimation in time series regression.
Journal of Nonparametric Statistics 30 (1), 1--27. (2018). - Leucht, A., Neumann, M. H., and Kreiss, J.-P.
A model specification test for GARCH(1,1) processes.
Scandinavian Journal of Statistics 42, 1167-1193. (2015). - Doukhan, P., Lang, G., Leucht, A. and Neumann, M. H.
Dependent wild bootstrap for the empirical process.pdf, 241 kb
Journal of Time Series Analysis 36, 290-314. (2015). - Fokianos, K. and Neumann, M. H.
A goodness-of-fit test for Poisson count processes.
Electronic Journal of Statistics 7, 793-819. (2013). - Leucht, A. and Neumann, M. H.
Dependent wild bootstrap for degenerate U- and V-statistics.
Journal of Multivariate Analysis 117, 257-280. (2013). - Neumann, M. H.
A central limit theorem for triangular arrays of weakly dependent random variables, with applications in statistics.
ESAIM: Probability and Statistics 17, 120-134. (2013). - Leucht, A. and Neumann, M. H.
Degenerate U- and V-statistics under ergodicity: asymptotics, bootstrap and applications in statistics.
Annals of the Institute of Statistical Mathematics 65 (2), 349-386. (2013). - Neumann, M. H.
Absolute regularity and ergodicity of Poisson count processes.
Bernoulli 17. 1268-1284. (2011). - Meister, A. and Neumann, M. H.
Deconvolution from non-standard error densities under replicated measurements.
Statistica Sinica 20, 1609-1636. (2009). - Leucht, A. and Neumann, M. H.
Consistency of general bootstrap methods for degenerate U- and V-type statistics.pdf, 754 kb
Journal of Multivariate Analysis 100, 1622-1633. (2009). - Neumann, M. H. and Reiß, M.
Nonparametric estimation for Lévy processes from low-frequency observations.pdf, 339 kb
Bernoulli 15, 223-248. (2008). - Kreiß, J.-P., Neumann, M. H., and Yao, Q.
Bootstrap tests for simple structures in nonparametric time series regression.pdf, 342 kb
Statistics and Its Interface 1, 367-380. (2008). - Neumann, M. H. and Paparoditis, E.
Simultaneous confidence bands in spectral density estimation.Externer Link
Biometrika 95, 381-397. (2008). - Doukhan, P. and Neumann, M. H.
The notion of ψ-weak dependence and its applications to bootstrapping time series.pdf, 319 kb
Probability Surveys 5, 146-168. (2008). - Neumann, M. H. and Paparoditis, E.
Goodness-of-fit tests for Markovian time series models: Central limit theory and bootstrap.
Bernoulli 14, 14-46. (2007). - Neumann, M. H.
Deconvolution from panel data with unknown error distribution.pdf, 208 kb
Journal of Multivariate Analysis 98, 1955-1968. (2007). - Doukhan, P. and Neumann, M. H.
Probability and moment inequalities for sums of weakly dependent random variables, with applications.pdf, 297 kb
Stochastic Processes and Their Applications 117, 878-903. (2007). - Neumann, M. H. and Thorarinsdottir, T. L.
Minimax estimation in nonparametric autoregression.pdf, 274 kb
Mathematical Methods of Statistics 15, 374-397. (2006). - Grama, I. G. and Neumann, M. H.
Asymptotic equivalence of nonparametric autoregression and nonparametric regression.pdf, 308 kb
Annals of Statistics 34, 1701-1732. (2006). - Kallabis, R. S. and Neumann, M. H.
An exponential inequality under weak dependence.
Bernoulli 12, 333-350. (2006). - Butucea, C. and Neumann, M. H.
Exact asymptotics for estimating the marginal density of discretely observed diffusion processes.
Bernoulli 11, 411-444. (2005). - Herwartz, H. and Neumann, M. H.
Bootstrap Inference in Systems of Single Equation Error Correction Models.
Journal of Econometrics 128, 165-193. (2005). - Franke, J., Neumann, M. H. and Stockis, J.-P.
Bootstrapping nonparametric estimators of the volatility function.
Journal of Econometrics 118, 189-218. (2004). - Franke, J., Kreiss, J.-P., Mammen, E., and Neumann, M. H.
Properties of the nonparametric autoregressive bootstrap.
Journal of Time Series Analysis 23, 555-585. (2002). - Neumann, M. H.
On robustness of model-based bootstrap schemes in nonparametric time series analysis.
Statistics 35, 1-40. (2001). - Dahlhaus, R. and Neumann, M. H.
Locally adaptive fitting of semiparametric models to nonstationary time series.
Stochastic Processes and Applications 91, 277-308. (2001). - von Sachs, R. and Neumann, M. H.
A wavelet-based test for stationarity.
Journal of Time Series Analysis 21, 597-613. (2000). - Franke, J. and Neumann, M. H.
Bootstrapping neural networks.
Neural Computation 12, 1929-1949. (2000). - Benkwitz, A., Lütkepohl, H. and Neumann, M. H.
Problems related to confidence intervals for impulse responses of autoregressive processes.
Econometric Reviews 19, 69-103. (2000). - Neumann, M. H.
Multivariate wavelet thresholding in anisotropic function spaces.
Statistica Sinica 10, 399-431. (2000). - Neumann, M. H. and Paparoditis, E.
On bootstrapping L2 -type statistics in density testing.
Statistics and Probabability Letters 50, 137-147. (2000). - Dahlhaus, R., Neumann, M. H. and von Sachs, R.
Nonlinear wavelet estimation of time-varying autoregressive processes.
Bernoulli 5, 873-906. (1999). - Neumann, M. H. and Polzehl, J.
Simultaneous bootstrap confidence bands in nonparametric regression.
Journal of Nonparametric Statistics 9, 307-333. (1998). - Klinke, S., Golubev, Yu., Härdle, W. and Neumann, M. H.
Teaching wavelets in Xplore.
Computational Statistics 13. 141-151. (1998). - Marron, J. S., Adak, S., Johnstone, I. M., Neumann, M. H., and Patil, P.
Exact risk analysis of wavelet regression.
Journal of Graphical and Computational Statistics 7, 278-309. (1998). - Neumann, M. H.
Strong approximation of density estimators from weakly dependent observations by density estimators from independent observations.
Annals of Statistics 26, 2014-2048. (1998). - Neumann, M. H. and Kreiss, J.-P.
Regression-type inference in nonparametric autoregression.
Annals of Statistics 26, 1570-1613. (1998). - Neumann, M. H.
Pointwise confidence intervals in nonparametric regression with heteroscedastic error structure.
Statistics 29, 1-36. (1997). - Neumann, M. H.
Optimal change-point estimation in inverse problems.
Scandinavian Journal of Statistics 24, 503-521. (1997). - Neumann, M. H.
On the effect of estimating the error density in nonparametric deconvolution.
Journal of Nonparametric Statistics 7, 307-330. (1997). - Hall, P., Marron, J. S., Neumann, M. H., and Titterington, D. M.
Curve estimation when the design density is low.
Annals of Statistics 25, 756-770. (1997). - Neumann, M. H. and von Sachs, R.
Wavelet thresholding in anisotropic function classes and application to adaptive estimation of evolutionary spectra.
Annals of Statistics 25, 38-76. (1997). - Neumann, M. H.
Spectral density estimation via nonlinear wavelet methods for stationary non-Gaussian time series.
Journal of Time Series Analysis 17, 601-633. (1996). - Neumann, M. H. and von Sachs, R.
Wavelet thresholding: beyond the Gaussian i.i.d. situation.
in Lecture Notes in Statistics: Wavelets and Statistics , A. Antoniadis ed., 301-329. (1995). - Neumann, M. H.
Discussion to the paper "Wavelet shrinkage: asymptopia?" by Donoho et al.,
Journal of the Royal Statistical Society Ser. B 57, 346-347. (1995). - Neumann, M. H. and Spokoiny, V. G.
On the efficiency of wavelet estimators under arbitrary error distributions.
Mathematical Methods of Statistics 4, 137-166. (1995). - Neumann, M. H.
Automatic bandwidth choice and confidence intervals in nonparametric regression.
Annals of Statistics 23, 1937-1959. (1995). - Neumann, M. H.
Fully data-driven nonparametric variance estimators.
Statistics 25, 189-212. (1994). - Neumann, M. H.
Second order asymptotic risks of smoothed linear estimators in nonparametric regression models.
Statistics 23, 217-236. (1992).
Andere Publikationen
- Doukhan, P., Leucht, A., and Neumann, M. H.
Mixing properties of non-stationary INGARCH(1,1) processes.
Manuscript. (2021). - Wechsung, M. and Neumann, M. H.
Nonparametric least squares estimation in integer-valued GARCH models.
Manuscript. (2020). - Doukhan, P., Neumann, M. H., and Truquet, L.
Stationarity and ergodic properties for some obserrvation-driven models in random environments.
Manuscript. (2020). - Fokianos, K., Leucht, A. and Neumann, M. H.
Multivariate isotonic time series regression.
Manuskript. (2016). - Herwartz, H. and Neumann, M. H.
A robust bootstrap approach to the Hausman test in stationary panel data models.
Preprint. (2006). - Neumann, M. H.
Discussion to Booth, Bühlmann and Wood.
Proceedings of the 52nd Session of the International Statistical Institute, Helsinki 1999, 97-98. (1999). - Neumann, M. H.
On the asymptotic efficiency of kernel estimators of regression.
Preprint No. 91-21, Humboldt University. (1991). - Neumann, M. H.
Asymptotic results for kernel estimators of the mean vector and the heteroscedastic variance vector without replications at the design points.
Seminarbericht No. 109, Humboldt University. (1990).
(ein Teil ist unter dem Titel "Fully data-driven nonparametric variance estimators" in Statistics 25, 189-212, 1994 erschienen)