Series approximation methods in statistics
type: Item
instance of: scholarly article
title: Series approximation methods in statistics
zbMATH Open document ID: 0797.62008
author: John Kolassa
published in: Lecture Notes in Statistics
publication date: 1994-05-30T00:00:00Z
review text: This book is focused on Edgeworth and saddlepoint approximations and related techniques not discussed in recent theoretical text books. Attention is paid to a rigorous consideration of Edgeworth and saddlepoint expansion limit theorems, especially for lattice distributions, and a survey of the more recent developments in this field. Saddlepoint methods of approximating densities and distribution functions for conditional distributions are investigated. As applications, approximation of densities and distribution functions of maximum likelihood estimators and likelihood ratio statistics are also considered. In the final chapter, computational tools are presented to help in the derivation and manipulation of these expansions.
Mathematics Subject Classification ID: 62E20
Mathematics Subject Classification ID: 62-02
Mathematics Subject Classification ID: 62E17
zbMATH DE Number: 578384
zbMATH Keywords: Edgeworth series
zbMATH Keywords: saddlepoint approximations
zbMATH Keywords: limit theorems
zbMATH Keywords: lattice distributions
zbMATH Keywords: conditional distributions
zbMATH Keywords: maximum likelihood estimators
zbMATH Keywords: likelihood ratio statistics
zbMATH Keywords: computational tools
reviewed by: Ken-ichi Yoshihara
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 578384