Exact Statistical Inference on Markov Chain Models
Author : Timothy Duane Johnson
Publisher :
Page : 534 pages
File Size : 45,61 MB
Release : 1997
Category :
ISBN :
Inference in Hidden Markov Models
Author : Olivier Cappé
Publisher : Springer Science & Business Media
Page : 656 pages
File Size : 42,19 MB
Release : 2006-04-12
Category : Mathematics
ISBN : 0387289828
Book Description
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.
Change-point Problems
Author : Edward G. Carlstein
Publisher : IMS
Page : 400 pages
File Size : 36,10 MB
Release : 1994
Category : Mathematics
ISBN : 9780940600348
Book Description
Probability, Statistics and Time
Author : M. S. Bartlett
Publisher : Springer
Page : 148 pages
File Size : 32,96 MB
Release : 1980-03-06
Category : Science
ISBN : 9780412222603
Book Description
Some years ago when I. assembled a number of general articles and lectures on probability and statistics, their publication (Essays in Probability and Statistics, Methuen, London, 1962) received a some what better reception than I had been led to expect of such a miscellany. I am consequently tempted to risk publishing this second collection, the title I have given it (taken from the first lecture) seeming to me to indicate a coherence in my articles which my publishers might otherwise be inclined to query. As in the first collection, the articles are reprinted chronologically, usually without comment. One exception is the third, not previously published and differing from the original spoken version both slightly where indicated in the text and by the addition of an Appendix. I apologize for the inevitable limitations due to date, and also for any occasional repetition of the discussion (e.g. on Bayesian methods in statistical inference). In particular, readers technically interested in the classification and use of nearest-neighbour models, a topic raised in Appendix II of the fourth article, should also refer to my monograph The Statistical Analysis of Spatial Pattern (Chapman and Hall, London, 1976), where a much more up-to-date account of these models will be found, and, incidentally, a further emphasis, if one is needed, of the common statistical theory of physics and biology. March 1975 M.S.B.
Handbook of Markov Chain Monte Carlo
Author : Steve Brooks
Publisher : CRC Press
Page : 620 pages
File Size : 38,92 MB
Release : 2011-05-10
Category : Mathematics
ISBN : 1420079425
Book Description
Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisherie
Non-negative Matrices and Markov Chains
Author : E. Seneta
Publisher : Springer Science & Business Media
Page : 295 pages
File Size : 10,6 MB
Release : 2006-07-02
Category : Mathematics
ISBN : 0387327924
Book Description
Since its inception by Perron and Frobenius, the theory of non-negative matrices has developed enormously and is now being used and extended in applied fields of study as diverse as probability theory, numerical analysis, demography, mathematical economics, and dynamic programming, while its development is still proceeding rapidly as a branch of pure mathematics in its own right. While there are books which cover this or that aspect of the theory, it is nevertheless not uncommon for workers in one or another branch of its development to be unaware of what is known in other branches, even though there is often formal overlap. One of the purposes of this book is to relate several aspects of the theory, insofar as this is possible. The author hopes that the book will be useful to mathematicians; but in particular to the workers in applied fields, so the mathematics has been kept as simple as could be managed. The mathematical requisites for reading it are: some knowledge of real-variable theory, and matrix theory; and a little knowledge of complex-variable; the emphasis is on real-variable methods. (There is only one part of the book, the second part of 55.5, which is of rather specialist interest, and requires deeper knowledge.) Appendices provide brief expositions of those areas of mathematics needed which may be less g- erally known to the average reader.
Statistical Inference and Simulation for Spatial Point Processes
Author : Jesper Moller
Publisher : CRC Press
Page : 320 pages
File Size : 33,78 MB
Release : 2003-09-25
Category : Mathematics
ISBN : 9780203496930
Book Description
Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.
Stochastic Epidemic Models with Inference
Author : Tom Britton
Publisher : Springer Nature
Page : 477 pages
File Size : 11,34 MB
Release : 2019-11-30
Category : Mathematics
ISBN : 3030309002
Book Description
Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.
Tools for Statistical Inference
Author : Martin A. Tanner
Publisher : Springer Science & Business Media
Page : 166 pages
File Size : 20,54 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1468401920
Book Description
This book provides a unified introduction to a variety of computational algorithms for likelihood and Bayesian inference. In this second edition, I have attempted to expand the treatment of many of the techniques dis cussed, as well as include important topics such as the Metropolis algorithm and methods for assessing the convergence of a Markov chain algorithm. Prerequisites for this book include an understanding of mathematical statistics at the level of Bickel and Doksum (1977), some understanding of the Bayesian approach as in Box and Tiao (1973), experience with condi tional inference at the level of Cox and Snell (1989) and exposure to statistical models as found in McCullagh and Neider (1989). I have chosen not to present the proofs of convergence or rates of convergence since these proofs may require substantial background in Markov chain theory which is beyond the scope ofthis book. However, references to these proofs are given. There has been an explosion of papers in the area of Markov chain Monte Carlo in the last five years. I have attempted to identify key references - though due to the volatility of the field some work may have been missed.
Selected Papers of Hirotugu Akaike
Author : Emanuel Parzen
Publisher : Springer Science & Business Media
Page : 432 pages
File Size : 27,11 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 146121694X
Book Description
The pioneering research of Hirotugu Akaike has an international reputation for profoundly affecting how data and time series are analyzed and modelled and is highly regarded by the statistical and technological communities of Japan and the world. His 1974 paper "A new look at the statistical model identification" (IEEE Trans Automatic Control, AC-19, 716-723) is one of the most frequently cited papers in the area of engineering, technology, and applied sciences (according to a 1981 Citation Classic of the Institute of Scientific Information). It introduced the broad scientific community to model identification using the methods of Akaike's criterion AIC. The AIC method is cited and applied in almost every area of physical and social science. The best way to learn about the seminal ideas of pioneering researchers is to read their original papers. This book reprints 29 papers of Akaike's more than 140 papers. This book of papers by Akaike is a tribute to his outstanding career and a service to provide students and researchers with access to Akaike's innovative and influential ideas and applications. To provide a commentary on the career of Akaike, the motivations of his ideas, and his many remarkable honors and prizes, this book reprints "A Conversation with Hirotugu Akaike" by David F. Findley and Emanuel Parzen, published in 1995 in the journal Statistical Science. This survey of Akaike's career provides each of us with a role model for how to have an impact on society by stimulating applied researchers to implement new statistical methods.
