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Author : Maurice George Kendall
Publisher :
Page : 458 pages
File Size : 15,84 MB
Release : 1963
Category : Mathematical statistics
ISBN :
Author : Maurice George Kendall
Publisher : Wiley-Interscience
Page : 712 pages
File Size : 38,73 MB
Release : 1994-06-30
Category : Business & Economics
ISBN :
This major revision contains a largely new chapter 7 providing an extensive discussion of the bivariate and multivariate versions of the standard distributions and families. Chapter 16 has been enlarged to cover multivariate sampling theory, an updated version of material previously found inthe old Volume III. The previous chapters 7 and 8 have been condensed into a single chapter providing an introduction to statistical inference. Elsewhere, major updates include new material on skewness and kurtosis, hazard rate distributions, the bootstrap, the evaluation of the multivariate normalintegral and ratios of quadratic forms. The new edition includes over 200 new references, 40 new exercises and 20 further examples in the main text. In addition, all the text examples have been given titles, and these are listed at the front of the book for easier reference.
Author : Maurice George Kendall
Publisher :
Page : 480 pages
File Size : 33,99 MB
Release : 1947
Category : Statistics
ISBN :
Author : Maurice George Kendall
Publisher :
Page : 492 pages
File Size : 21,9 MB
Release : 1977
Category : Mathematical statistics
ISBN :
V.1: Distribution theory; v.2: Inference and relationship; v.3: Design and analysis, and time-series.
Author : Thomas A. Severini
Publisher : Cambridge University Press
Page : 3 pages
File Size : 40,34 MB
Release : 2005-08-08
Category : Mathematics
ISBN : 1139446118
This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.
Author : Mark J. Schervish
Publisher : Springer Science & Business Media
Page : 732 pages
File Size : 18,68 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1461242509
The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.
Author : Alan Stuart
Publisher : Wiley
Page : 250 pages
File Size : 31,59 MB
Release : 2009-02-24
Category : Mathematics
ISBN : 9780340814932
This 3-volume set offers the complete, classic Kendall's Advanced Theory of Statistics in a single, value-for-money pack. The latest set includes the brand new second edition of the popular 'Volume 2B: Bayesian Inference', along with the sixth editions of 'Volume 1: Distribution Theory' and 'Volume 2A: Classical Inference and the Linear Model'.
Author : J.J. Duistermaat
Publisher : Springer Science & Business Media
Page : 455 pages
File Size : 33,25 MB
Release : 2010-08-09
Category : Mathematics
ISBN : 0817646752
This textbook is an application-oriented introduction to the theory of distributions, a powerful tool used in mathematical analysis. The treatment emphasizes applications that relate distributions to linear partial differential equations and Fourier analysis problems found in mechanics, optics, quantum mechanics, quantum field theory, and signal analysis. The book is motivated by many exercises, hints, and solutions that guide the reader along a path requiring only a minimal mathematical background.
Author : F. G. Friedlander
Publisher : Cambridge University Press
Page : 192 pages
File Size : 30,99 MB
Release : 1998
Category : Mathematics
ISBN : 9780521649711
The second edition of a classic graduate text on the theory of distributions.
Author : James C. Fu
Publisher : World Scientific
Page : 174 pages
File Size : 24,26 MB
Release : 2003
Category : Mathematics
ISBN : 9810245874
A rigorous, comprehensive introduction to the finite Markov chain imbedding technique for studying the distributions of runs and patterns from a unified and intuitive viewpoint, away from the lines of traditional combinatorics.