On construction of confidence intervals for a mean of dependent data
Discussiones Mathematicae. Probability and Statistics, Tome 21 (2001) no. 2, pp. 121-147.

Voir la notice de l'article provenant de la source Library of Science

In the report, the performance of several methods of constructing confidence intervals for a mean of stationary sequence is investigated using extensive simulation study. The studied approaches are sample reuse block methods which do not resort to bootstrap. It turns out that the performance of some known methods strongly depends on a model under consideration and on whether a two-sided or one-sided interval is used. Among the methods studied, the block method based on weak convergence result by Wu (2001) seems to perform most stably.
Keywords: confidence intervals, short-range dependence, reuse block methods, normal approximation, iterated random function sequence
@article{DMPS_2001_21_2_a4,
     author = {\'Cwik, Jan and Mielniczuk, Jan},
     title = {On construction of confidence intervals for a mean of dependent data},
     journal = {Discussiones Mathematicae. Probability and Statistics},
     pages = {121--147},
     publisher = {mathdoc},
     volume = {21},
     number = {2},
     year = {2001},
     zbl = {1006.62044},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/DMPS_2001_21_2_a4/}
}
TY  - JOUR
AU  - Ćwik, Jan
AU  - Mielniczuk, Jan
TI  - On construction of confidence intervals for a mean of dependent data
JO  - Discussiones Mathematicae. Probability and Statistics
PY  - 2001
SP  - 121
EP  - 147
VL  - 21
IS  - 2
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/DMPS_2001_21_2_a4/
LA  - en
ID  - DMPS_2001_21_2_a4
ER  - 
%0 Journal Article
%A Ćwik, Jan
%A Mielniczuk, Jan
%T On construction of confidence intervals for a mean of dependent data
%J Discussiones Mathematicae. Probability and Statistics
%D 2001
%P 121-147
%V 21
%N 2
%I mathdoc
%U http://geodesic.mathdoc.fr/item/DMPS_2001_21_2_a4/
%G en
%F DMPS_2001_21_2_a4
Ćwik, Jan; Mielniczuk, Jan. On construction of confidence intervals for a mean of dependent data. Discussiones Mathematicae. Probability and Statistics, Tome 21 (2001) no. 2, pp. 121-147. http://geodesic.mathdoc.fr/item/DMPS_2001_21_2_a4/

[1] J. Beran, Statistics for Long-Memory Processes, Chapman and Hall, New York 1994.

[2] G. Box and G. Jenkins, Time Series Analysis, Holden Day 1976.

[3] P. Brockwell and R. Davis, Time Series: Theory and Methods, 6th edition, Springer 1998.

[4] J. Ćwik, J. Koronacki and J. Mielniczuk, Testing for a difference between conditional variance functions of nonlinear time series, Control and Cybernetics 29 (2000), 33-50.

[5] E. Carlstein, The use of subseries methods for estimating the variance of a general statistics from a stationary time series, Ann. Statist 14 (1986), 1171-1179.

[6] S. Csörgo, and J. Mielniczuk, Close short-range dependent sums and regression estimation, Acta. Sci. Math. (Szeged) 60 (1995), 177-196.

[7] A. Davison and P. Hall, On studentizing and blocking methods for implementing the bootstrap with dependent data, Austr. J. Statist. 35 (1992), 215-224.

[8] P. Diaconis and D. Freedman, Iterated random functions, SIAM Review 41 (1999), 41-76.

[9] P. Hall and B. Jing, On sample reuse methods for dependent data, J. R. Statist. Soc. B (1996), 727-737.

[10] H.C. Ho and T. Hsing, Limit theorems for functionals of moving averages, Ann. Probab. 25 (1997), 1636-1669.

[11] H. Künsch, The jacknife and the bootstrap for general stationary observations, Ann. Statist. 17 (1989), 1217-1241.

[12] Politis and Romano, Large sample confidence regions based on subsamples under minimal asuumptions, Ann. Statist. 22 (1994), 2031-2050.

[13] M. Rosenblatt, Stationary Sequences and Random Fields, Birkhäuser, Boston 1985.

[14] J. Shao and D. Tu, The Jacknife and Bootstrap, Springer 1995.

[15] K. Singh, On the asymptotic accuracy of Efron's bootstrap, Ann. Statist. 9 (1981), 1187-1195.

[16] W.B. Wu, Studies in time series and random dynamics, Ph. D. thesis, University of Michigan 2001.