Electronic Journal of Statistics

Bootstrap of means under stratified sampling

Odile Pons

Full-text: Open access

Abstract

In a two-stage cluster sampling procedure, n random populations are drawn independently from independent populations and a sub-sample of observations is taken in each of them. The estimator of the general mean of the observed variables is asymptotically Gaussian and the asymptotic distributions of several bootstrap versions of the normalized and studentized statistics are studied. A weighted population resampling provides a good approximation and its accuracy depends on the convergence rate of the sample size of the populations.

Article information

Source
Electron. J. Statist., Volume 1 (2007), 381-391.

Dates
First available in Project Euclid: 20 September 2007

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1190312984

Digital Object Identifier
doi:10.1214/07-EJS033

Mathematical Reviews number (MathSciNet)
MR2346004

Zentralblatt MATH identifier
1140.62316

Subjects
Primary: 62F12: Asymptotic properties of estimators 60F40

Keywords
Cluster sampling bootstrap second-order asymptotic

Citation

Pons, Odile. Bootstrap of means under stratified sampling. Electron. J. Statist. 1 (2007), 381--391. doi:10.1214/07-EJS033. https://projecteuclid.org/euclid.ejs/1190312984


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