Statistical Inference
The Minimum Distance Approach
Published on 22. June 2011
429 pages
978-1-040-20464-1 (ISBN)
Description
In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Stati
Reviews / Votes
"The book is an excellent and thorough outline of work in the area. It would provide an ideal volume for someone who plans to undertake research in the area."-International Statistical Review, 2013
"The book provides a comprehensive overview of the theory of density-based minimum distance methods and it is well written and easy to read and understand. The book is well suited for graduate students, professionals and researchers not only in statistics but also in biosciences, engineering and various other fields where statistical inference plays a fundamental role."
-Alex Karagrigoriou, Journal of Applied Statistics, 2012
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
File size
3,38 MB
ISBN-13
978-1-040-20464-1 (9781040204641)
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Schweitzer Classification
Other editions
Additional editions
Ayanendranath Basu | Hiroyuki Shioya | Chanseok Park
Statistical Inference
The Minimum Distance Approach
Book
01/2023
1st Edition
Chapman & Hall/CRC
€76.94
Shipment within 10-20 days
Ayanendranath Basu | Hiroyuki Shioya | Chanseok Park
Statistical Inference
The Minimum Distance Approach
Book
06/2011
1st Edition
Chapman & Hall/CRC
€233.00
Shipment within 15-20 days
Persons
Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park
Content
Introduction. Statistical Distances. Continuous Models. Measures of Robustness and Computational Issues. The Hypothesis Testing Problem. Techniques for Inlier Modification. Weighted Likelihood Estimation. Multinomial Goodness-of-fit Testing. The Density Power Divergence. Other Applications. Distance Measures in Information and Engineering. Applications to Other Models.
