Small sample properties of bootstrap

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Author
Bernhardt, Stefan
Date
1988-09Advisor
Jayachandran, Toke
Second Reader
Read, Robert R.
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Show full item recordAbstract
The Bootstrap method is a nonparametric statistical technique for estimating the sampling
distribution of estimators of unknown parameters. While the asymptotic theory for
bootstrap is well established, this thesis investigates the behavior of the bootstrap for
small sample sizes. For the exponential distribution and for normal linear regression the
bootstrap estimates of 'he parameters and their variances are compared with the theoretical
sampling distributions. The small sample properties of bootstrap confidence intervals
using the percentile method and the bias-corrected percentile method are also
investigated.
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