Theory of Statistical Estimation: Contributions to Higher Order Asymptotics and Non-Regular Cases

Author:   Masafumi Akahira
Publisher:   Springer Verlag, Singapore
ISBN:  

9789819553389


Pages:   370
Publication Date:   15 May 2026
Format:   Hardback
Availability:   Not yet available   Availability explained
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Theory of Statistical Estimation: Contributions to Higher Order Asymptotics and Non-Regular Cases


Overview

This book is a reconstruction of Masafumi Akahira’s works on statistical estimation and its related fields, especially higher order asymptotics and non-regular cases with consideration based on information amounts. There have been few books on higher order asymptotics and non-regular cases, but the book helps the reader to understand the meaning and implications of the hierarchical structure of higher order asymptotics and gives some insights into the structure of non-regular estimation.  After the results on the second and third order asymptotic efficiency in the volume entitled “Joint Statistical Papers of Akahira and Takeuchi” are summarized, the positive resolution of the conjecture “third order efficiency implies fourth order efficiency” of J. K. Ghosh is described, from which the fourth order asymptotic efficiency of the bias-adjusted maximum likelihood estimator and the bias-adjusted generalized Bayes estimator is shown. In non-regular situations, the (maximum) order of consistency and the (second order) asymptotic sufficiency are discussed including the view of loss of information, and in regular cases, the asymptotic deficiency of asymptotically efficient estimators is stated. For a truncated family of distributions, the influence of a nuisance parameter on the estimation of the interest parameter is investigated through maximum likelihood estimators. Also discussed is the higher order sequential estimation with the Bhattacharyya type bound, including the presence of a nuisance parameter.  In interval estimation, a systematic method of the construction of a confidence interval for the difference between means is discussed including the Behrens–Fisher type problem, and also ordinary, Bayesian, likelihood ratio and combined Bayesian–frequentist type confidence intervals for a positive parameter are provided and compared. Further, the higher order approximations to percentage points of the non-central t-distribution and the distribution of a non-central t-statistic without the normality assumptions are given. Finally, the large deviation efficiency and large deviation approximations are discussed up to the higher order.  Masafumi Akahira is Professor Emeritus at the University of Tsukuba. He has served as Vice President of the University of Tsukuba and President of the Japan Statistical Society.   

Full Product Details

Author:   Masafumi Akahira
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
ISBN:  

9789819553389


ISBN 10:   9819553385
Pages:   370
Publication Date:   15 May 2026
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Order of Consistency and Its Maximum Order.- Asymptotic Sufficiency and Asymptotic Efficiency.- Loss of Information.- Higher Order Asymptotics in Estimation.- Asymptotic Deficiency and Normalized deficiency.-  Maximum Likelihood Estimation for a One-sided Truncated Family of Distributions.-  Higher Order Sequential Estimation.- Interval Estimation.-  Information Inequalities in Non-Regular Cases.- Higher Order Approximations to a Percentage Point.- Large Deviation Efficiency and Large Deviation Approximations up to the Higher Order.

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Author Information

Masafumi Akahira, Institute of Mathematics, University of Tsukuba

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Latest Reading Guide

April RG 26_2

 

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