Statistical Inference - The Minimum Distance Approach

List of contents

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.

About the author

Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park

Summary

This book gives a comprehensive account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of rob

Product details

• Authors: Ayanendranath Basu, Ayanendranath Shioya Basu, Basu Ayanendranath, Chanseok Park, Park Chanseok, Hiroyuki Shioya, Shioya Hiroyuki
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 21.01.2023
• EAN: 9781032477633
• ISBN: 978-1-0-3247763-3
• No. of pages: 430
• Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; COMPUTERS / General, MATHEMATICS / Probability & Statistics / General, environmental science, engineering & technology, Probability & statistics, Automatic control engineering, Probability and statistics, Environmental science, engineering and technology