Implementation of Saddlepoint Approximations in Resampling
Problems
Angelo J. Canty and A. C. Davison
Abstract
In many situations, saddlepoint approximations can replace the Monte Carlo
simulation typically used to find the bootstrap distribution of a statistic.
We explain how bootstrap and permutation distributions can be expressed as
conditional distributions and how methods for linear programming and for
fitting generalized linear models can be used to find saddlepoint
approximations to these distributions. The ideas are illustrated using an
example from insurance.
Keywords:
Bootstrap; exponential family; generalized linear model;
saddlepoint approximation; Simplex method; Sparre Anderson model; test
inversion.
This article was published in Statistics and Computing (1999),
9, 9-15.
This page is maintained by Angelo Canty,
cantya@mcmaster.ca
Last updated on July 23, 2001