Bootstrap variance estimation for complex survey data: a Quasi Monte Carlo approach

Author:

Aidara Cherif Ahmat Tidiane

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Reference12 articles.

1. Dutang, C. and Savicky, P. (2012). randtoolbox: Generating and testing random numbers. R package version 1.11.

2. Faure, H. (1982). Discrepance de suites associees a un systeme de numeration (en dimension s). Acta Arith., 41, 337–351.

3. Halton, J. (1960). On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals. Numer. Math., 2 84–90.

4. Hess, S. and Polak, J. (2003). An alternative method to the scrambled Halton sequence for removing correlation between standard Halton sequences in high dimensions. European Regional Science Conference Jyvskyl-2003.

5. Kolenikov, S. (2007). Applications of quasi-Monte Carlo methods in inference for complex survey data. In Proceedings of the Survey Reseacrh Methods Section of ASA

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