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This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

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Activity Number: 252
Type: Contributed
Date/Time: Tuesday, July 31, 2007 : 8:30 AM to 10:20 AM
Sponsor: Section on Survey Research Methods
Abstract - #309256
Title: Quasi--Monte Carlo Methods for Variance Estimation
Author(s): Stanislav Kolenikov*+
Companies: University of Missouri-Columbia
Address: 146 Middlebush Hall, Columbia, MO, 65211,
Keywords: design-based inference ; balanced repeated replication ; bootstrap ; quasi Monte Carlo ; Halton sequence
Abstract:

In this talk, I shall consider the application of quasi-Monte Carlo tools, such as Halton sequences, to create approximately balanced replication designs. The QMC methods are designed to simulate points in multidimensional unit cubes with coverage asymptotically more uniform that that of the standard Monte Carlo. I will adopt those methods to generate replication designs that occupy an intermediate position between highly balanced designs such as BRR, and random replication designs such as the bootstrap. Thus the resulting designs can be viewed as a viable alternative to the extensions of BRR based on mixed orthogonal arrays, or to the balanced bootstrap.

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Revised September, 2007