BS2 Further Statistical Inference HT08 - Lecture 11

Saddle-point approximations and asymptotics of the MLE

This lecture discusses the more accurate asymptotics of  maximum likelihood estimation. In particular it exploits the Edgeworth expansion of the density of a sum of random variables and tilting to find accurate approximations to the distribution of an MLE conditional on an ancillary statistic. Corresponding material can be found in Young and Smith (2005), sections 9.5, 9.6, and 9.8

Overheads

Next lecture

Previous lecture

Course overview


Last updated: Wednesday, 02 April 2008 11:30Steffen L. Lauritzen