Department of Statistics, The Ohio State University
Statistics and Biostatistics Colloquium Series

In this talk we review the linkage between bootstrap estimation and quantile function estimation. We then outline a new quantile function estimator called the tail extrapolation quantile function estimator. The estimator behaves asymptotically exactly the same as the standard linear interpolation estimator. For finite samples there is small correction towards estimating the extreme quantiles. We illustrate that by employing this new estimator we can greatly improve the coverage probabilities of the standard bootstrap percentile confidence intervals. This approach does not require complicated calculations and hence it should appeal to the statistical practitioner.

Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.