Thesis Title

Bias Reduction of Estimates By Bootstrap Method

Date of Graduation

Spring 1995

Degree

Master of Science in Mathematics

Department

Mathematics

Committee Chair

George Mathew

Subject Categories

Mathematics

Abstract

In general it is desirable to have unbiased estimators for parameters of a probability distribution function. However, there are several estimators which are not unbiased. In this thesis, we show by direct computation that the bias of the bootstrap estimate of μ⁴ can be reduced, where μ is the mean of the population. We consider both nonparametric and parametric cases. In the parametric case, the bias of the bootstrap estimate is computed for normal, exponential and Poisson distributions.

Copyright

© Linda J. Schuchman

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Dissertation/Thesis

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