Asymptotic Theory of Statistics and Probability

Asymptotic Theory of Statistics and Probability
Author: Anirban DasGupta
Publisher: Springer Science & Business Media
Total Pages: 727
Release: 2008-02-06
Genre: Mathematics
ISBN: 0387759719

This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique in its detailed coverage of fundamental topics. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. There is no other book in large sample theory that matches this book in coverage, exercises and examples, bibliography, and lucid conceptual discussion of issues and theorems.

Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence

Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence
Author: David L. Dowe
Publisher: Springer
Total Pages: 457
Release: 2013-10-22
Genre: Computers
ISBN: 3642449581

Algorithmic probability and friends: Proceedings of the Ray Solomonoff 85th memorial conference is a collection of original work and surveys. The Solomonoff 85th memorial conference was held at Monash University's Clayton campus in Melbourne, Australia as a tribute to pioneer, Ray Solomonoff (1926-2009), honouring his various pioneering works - most particularly, his revolutionary insight in the early 1960s that the universality of Universal Turing Machines (UTMs) could be used for universal Bayesian prediction and artificial intelligence (machine learning). This work continues to increasingly influence and under-pin statistics, econometrics, machine learning, data mining, inductive inference, search algorithms, data compression, theories of (general) intelligence and philosophy of science - and applications of these areas. Ray not only envisioned this as the path to genuine artificial intelligence, but also, still in the 1960s, anticipated stages of progress in machine intelligence which would ultimately lead to machines surpassing human intelligence. Ray warned of the need to anticipate and discuss the potential consequences - and dangers - sooner rather than later. Possibly foremostly, Ray Solomonoff was a fine, happy, frugal and adventurous human being of gentle resolve who managed to fund himself while electing to conduct so much of his paradigm-changing research outside of the university system. The volume contains 35 papers pertaining to the abovementioned topics in tribute to Ray Solomonoff and his legacy.

Multivariate T-Distributions and Their Applications

Multivariate T-Distributions and Their Applications
Author: Samuel Kotz
Publisher: Cambridge University Press
Total Pages: 296
Release: 2004-02-16
Genre: Mathematics
ISBN: 9780521826549

Almost all the results available in the literature on multivariate t-distributions published in the last 50 years are now collected together in this comprehensive reference. Because these distributions are becoming more prominent in many applications, this book is a must for any serious researcher or consultant working in multivariate analysis and statistical distributions. Much of this material has never before appeared in book form. The first part of the book emphasizes theoretical results of a probabilistic nature. In the second part of the book, these are supplemented by a variety of statistical aspects. Various generalizations and applications are dealt with in the final chapters. The material on estimation and regression models is of special value for practitioners in statistics and economics. A comprehensive bibliography of over 350 references is included.

Full Bayesian Significance Test

Full Bayesian Significance Test
Author: Carlos Alberto de Bragança Pereira
Publisher:
Total Pages: 14
Release: 2000
Genre: Bayesian statistical decision theory
ISBN:

Abstract: "The Full Bayesian Significance Test (FBST) for precise hypotheses is presented, with some applications relevant to Biology. The FBST is an alternative to significance tests or, equivalently, to p-values. In the FBST we compute the evidence of the precise hypothesis. This evidence is the probability of the complement of a credible set 'tangent' to the sub-manifold (of the parameter space) that defines the null hypothesis. We use the FBST in applications arising in population dynamics, genetics and biology, like testing the Behrens-Fisher problem, coefficients of variation and Hardy-Weinberg equilibrium."