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On the Equivalence of Statistical Distances for Isotropic Convex Measures
Author: Puja Pandey
Publisher:
Published: 2023
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOK →conjecture hold for log-concave measures and convex body. The third chapter provides a concise overview of the statistical distances whose comparability will be further explored. In the fourth chapter, I offer a succinct demonstration of all the key findings we have derived for convex measures, establishing the comparability between different statistical distances. Upon establishing these findings for continuous probability measures, I recognized the presence of discrete probability measures. In the fifth chapter, I have contemplated quantitative comparisons between the classical distances for discrete probability distributions in the class of log-concave measures. There is a rich theory for continuous log-concave measure, however much less has been done for discrete convex measures. There is a vast concepts waiting to be studied and explored in this field. The concluding chapter summarizes the main findings and conclusions, highlighting potential research problems and approach for exploration pertaining to these measures.
Statistical Inference
Author: Ayanendranath Basu
Publisher: CRC Press
Published: 2011-06-22
Total Pages: 424
ISBN-13: 1420099663
DOWNLOAD EBOOK →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
Statistical Inference for Engineers and Data Scientists
Author: Pierre Moulin
Publisher: Cambridge University Press
Published: 2019
Total Pages: 423
ISBN-13: 1107185920
DOWNLOAD EBOOK →A mathematically accessible textbook introducing all the tools needed to address modern inference problems in engineering and data science.
Geometry and Statistics
Author:
Publisher: Academic Press
Published: 2022-07-15
Total Pages: 490
ISBN-13: 0323913466
DOWNLOAD EBOOK →Geometry and Statistics, Volume 46 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Geometry and Statistics
Evidential Statistics, Model Identification, and Science
Author: Mark Louis Taper
Publisher: Frontiers Media SA
Published: 2022-02-15
Total Pages: 238
ISBN-13: 288974406X
DOWNLOAD EBOOK →Convex Functions
Author: Jonathan M. Borwein
Publisher: Cambridge University Press
Published: 2010-01-14
Total Pages: 533
ISBN-13: 0521850053
DOWNLOAD EBOOK →The product of a collaboration of over 15 years, this volume is unique because it focuses on convex functions themselves, rather than on convex analysis. The authors explore the various classes and their characteristics, treating convex functions in both Euclidean and Banach spaces.
Handbook of Fitting Statistical Distributions with R
Author: Zaven A. Karian
Publisher: CRC Press
Published: 2016-04-19
Total Pages: 1722
ISBN-13: 1584887125
DOWNLOAD EBOOK →With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods
Probability for Statistics and Machine Learning
Author: Anirban DasGupta
Publisher: Springer Science & Business Media
Published: 2011-05-17
Total Pages: 796
ISBN-13: 1441996346
DOWNLOAD EBOOK →This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.
Information Theory and Statistics
Author: Imre Csiszár
Publisher: Now Publishers Inc
Published: 2004
Total Pages: 128
ISBN-13: 9781933019055
DOWNLOAD EBOOK →Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an "information geometry" background. Also, an introduction is provided to the theory of universal coding, and to statistical inference via the minimum description length principle motivated by that theory. The tutorial does not assume the reader has an in-depth knowledge of Information Theory or statistics. As such, Information Theory and Statistics: A Tutorial, is an excellent introductory text to this highly-important topic in mathematics, computer science and electrical engineering. It provides both students and researchers with an invaluable resource to quickly get up to speed in the field.
