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Author : Timothy Duane Johnson
Publisher :
ISBN 13 :
Total Pages : 534 pages
Book Rating : 4.:/5 ( download)
Download or read book Exact Statistical Inference on Markov Chain Models written by Timothy Duane Johnson and published by . This book was released on 1997 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Olivier Cappé
Publisher : Springer Science & Business Media
ISBN 13 : 0387289828
Total Pages : 656 pages
Book Rating : 4.3/5 (872 download)
Download or read book Inference in Hidden Markov Models written by Olivier Cappé and published by Springer Science & Business Media. This book was released on 2006-04-12 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Patrick Billingsley
Publisher :
ISBN 13 :
Total Pages : 100 pages
Book Rating : 4.3/5 (91 download)
Download or read book Statistical Inference for Markov Processes written by Patrick Billingsley and published by . This book was released on 1961 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Romain Azais
Publisher : John Wiley & Sons
ISBN 13 : 1119544092
Total Pages : 300 pages
Book Rating : 4.1/5 (195 download)
Download or read book Statistical Inference for Piecewise-deterministic Markov Processes written by Romain Azais and published by John Wiley & Sons. This book was released on 2018-07-30 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple yet challenging models to study. Nevertheless, the issue of statistical estimation of the parameters ruling the jump mechanism is far from trivial. Responding to new developments in the field as well as to current research interests and needs, Statistical inference for piecewise-deterministic Markov processes offers a detailed and comprehensive survey of state-of-the-art results. It covers a wide range of general processes as well as applied models. The present book also dwells on statistics in the context of Markov chains, since piecewise-deterministic Markov processes are characterized by an embedded Markov chain corresponding to the position of the process right after the jumps.
Author : Said Mohamed Rujbani
Publisher :
ISBN 13 :
Total Pages : 226 pages
Book Rating : 4.3/5 (121 download)
Download or read book Statistical Inference in Markov Chains Using the Principal of Minimum Discrimination Information written by Said Mohamed Rujbani and published by . This book was released on 1979 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David Zamar
Publisher :
ISBN 13 :
Total Pages : 102 pages
Book Rating : 4.:/5 (783 download)
Download or read book Monte Carlo Markov Chain Exact Inference for Binomial Regression Models written by David Zamar and published by . This book was released on 2006 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current methods for conducting exact inference for logistic regression are not capable of handling large data sets due to memory constraints caused by storing large networks. We provide and implement an algorithm which is capable of conducting (approximate) exact inference for large data sets. Various application fields, such as genetic epidemiology, in which logistic regression models are fit to larger data sets that are sparse or unbalanced may benefit from this work. We illustrate our method by applying it to a diabetes data set which could not be analyzed using existing methods implemented in software packages such as LogXact and SAS. We include a listing of our code along with documented instructions and examples of all user methods. The code will be submitted to the Comprehensive R Archive Network as a freely-available R package after further testing.
Author : Dani Gamerman
Publisher : CRC Press
ISBN 13 : 9780412818202
Total Pages : 264 pages
Book Rating : 4.8/5 (182 download)
Download or read book Markov Chain Monte Carlo written by Dani Gamerman and published by CRC Press. This book was released on 1997-10-01 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridging the gap between research and application, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference provides a concise, and integrated account of Markov chain Monte Carlo (MCMC) for performing Bayesian inference. This volume, which was developed from a short course taught by the author at a meeting of Brazilian statisticians and probabilists, retains the didactic character of the original course text. The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. It describes each component of the theory in detail and outlines related software, which is of particular benefit to applied scientists.
Author : Dani Gamerman
Publisher : CRC Press
ISBN 13 : 148229642X
Total Pages : 342 pages
Book Rating : 4.4/5 (822 download)
Download or read book Markov Chain Monte Carlo written by Dani Gamerman and published by CRC Press. This book was released on 2006-05-10 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applications, Markov Chain Monte Carlo: Stochastic Simul
Author : Iain L. MacDonald
Publisher : CRC Press
ISBN 13 : 9780412558504
Total Pages : 256 pages
Book Rating : 4.5/5 (585 download)
Download or read book Hidden Markov and Other Models for Discrete- valued Time Series written by Iain L. MacDonald and published by CRC Press. This book was released on 1997-01-01 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete-valued time series are common in practice, but methods for their analysis are not well-known. In recent years, methods have been developed which are specifically designed for the analysis of discrete-valued time series. Hidden Markov and Other Models for Discrete-Valued Time Series introduces a new, versatile, and computationally tractable class of models, the "hidden Markov" models. It presents a detailed account of these models, then applies them to data from a wide range of diverse subject areas, including medicine, climatology, and geophysics. This book will be invaluable to researchers and postgraduate and senior undergraduate students in statistics. Researchers and applied statisticians who analyze time series data in medicine, animal behavior, hydrology, and sociology will also find this information useful.
Author : Shiler Khedri
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (824 download)
Download or read book Markov Chain Monte Carlo Methods for Exact Tests in Contingency Tables written by Shiler Khedri and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is mainly concerned with conditional inference for contingency tables, where the MCMC method is used to take a sample of the conditional distribution. One of the most common models to be investigated in contingency tables is the independence model. Classic test statistics for testing the independence hypothesis, Pearson and likelihood chi-square statistics rely on large sample distributions. The large sample distribution does not provide a good approximation when the sample size is small. The Fisher exact test is an alternative method which enables us to compute the exact p-value for testing the independence hypothesis. For contingency tables of large dimension, the Fisher exact test is not practical as it requires counting all tables in the sample space. We will review some enumeration methods which do not require us to count all tables in the sample space. However, these methods would also fail to compute the exact p-value for contingency tables of large dimensions. \cite{DiacStur98} introduced a method based on the Grobner basis. It is quite complicated to compute the Grobner basis for contingency tables as it is different for each individual table, not only for different sizes of table. We also review the method introduced by \citet{AokiTake03} using the minimal Markov basis for some particular tables. \cite{BuneBesa00} provided an algorithm using the most fundamental move to make the irreducible Markov chain over the sample space, defining an extra space. The algorithm is only introduced for $2\times J \times K$ tables using the Rasch model. We introduce direct proof for irreducibility of the Markov chain achieved by the Bunea and Besag algorithm. This is then used to prove that \cite{BuneBesa00} approach can be applied for some tables of higher dimensions, such as $3\times 3\times K$ and $3\times 4 \times 4$. The efficiency of the Bunea and Besag approach is extensively investigated for many different settings such as for tables of low/moderate/large dimensions, tables with special zero pattern, etc. The efficiency of algorithms is measured based on the effective sample size of the MCMC sample. We use two different metrics to penalise the effective sample size: running time of the algorithm and total number of bits used. These measures are also used to compute the efficiency of an adjustment of the Bunea and Besag algorithm which show that it outperforms the the original algorithm for some settings.
Author : Peter Olofsson
Publisher : John Wiley & Sons
ISBN 13 : 1118231325
Total Pages : 573 pages
Book Rating : 4.1/5 (182 download)
Download or read book Probability, Statistics, and Stochastic Processes written by Peter Olofsson and published by John Wiley & Sons. This book was released on 2012-05-04 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition ". . . an excellent textbook . . . well organized and neatly written." —Mathematical Reviews ". . . amazingly interesting . . ." —Technometrics Thoroughly updated to showcase the interrelationships between probability, statistics, and stochastic processes, Probability, Statistics, and Stochastic Processes, Second Edition prepares readers to collect, analyze, and characterize data in their chosen fields. Beginning with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes on to present limit theorems and simulation. The authors combine a rigorous, calculus-based development of theory with an intuitive approach that appeals to readers' sense of reason and logic. Including more than 400 examples that help illustrate concepts and theory, the Second Edition features new material on statistical inference and a wealth of newly added topics, including: Consistency of point estimators Large sample theory Bootstrap simulation Multiple hypothesis testing Fisher's exact test and Kolmogorov-Smirnov test Martingales, renewal processes, and Brownian motion One-way analysis of variance and the general linear model Extensively class-tested to ensure an accessible presentation, Probability, Statistics, and Stochastic Processes, Second Edition is an excellent book for courses on probability and statistics at the upper-undergraduate level. The book is also an ideal resource for scientists and engineers in the fields of statistics, mathematics, industrial management, and engineering.
Author : Walter Zucchini
Publisher : CRC Press
ISBN 13 : 1315355205
Total Pages : 263 pages
Book Rating : 4.3/5 (153 download)
Download or read book Hidden Markov Models for Time Series written by Walter Zucchini and published by CRC Press. This book was released on 2017-12-19 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Author : Sai-Sing Lin
Publisher :
ISBN 13 :
Total Pages : 84 pages
Book Rating : 4.:/5 (31 download)
Download or read book Statistical Inference about Markov Chains written by Sai-Sing Lin and published by . This book was released on 1966 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Edward G. Carlstein
Publisher : IMS
ISBN 13 : 9780940600348
Total Pages : 400 pages
Book Rating : 4.6/5 (3 download)
Download or read book Change-point Problems written by Edward G. Carlstein and published by IMS. This book was released on 1994 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bernhard Schipp
Publisher : Springer Science & Business Media
ISBN 13 : 3790821217
Total Pages : 438 pages
Book Rating : 4.7/5 (98 download)
Download or read book Statistical Inference, Econometric Analysis and Matrix Algebra written by Bernhard Schipp and published by Springer Science & Business Media. This book was released on 2008-11-27 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Festschrift is dedicated to Götz Trenkler on the occasion of his 65th birthday. As can be seen from the long list of contributions, Götz has had and still has an enormous range of interests, and colleagues to share these interests with. He is a leading expert in linear models with a particular focus on matrix algebra in its relation to statistics. He has published in almost all major statistics and matrix theory journals. His research activities also include other areas (like nonparametrics, statistics and sports, combination of forecasts and magic squares, just to mention afew). Götz Trenkler was born in Dresden in 1943. After his school years in East G- many and West-Berlin, he obtained a Diploma in Mathematics from Free University of Berlin (1970), where he also discovered his interest in Mathematical Statistics. In 1973, he completed his Ph.D. with a thesis titled: On a distance-generating fu- tion of probability measures. He then moved on to the University of Hannover to become Lecturer and to write a habilitation-thesis (submitted 1979) on alternatives to the Ordinary Least Squares estimator in the Linear Regression Model, a topic that would become his predominant ?eld of research in the years to come.
Author : Gerhard Winkler
Publisher : Springer
ISBN 13 : 9783642629112
Total Pages : 0 pages
Book Rating : 4.6/5 (291 download)
Download or read book Image Analysis, Random Fields and Markov Chain Monte Carlo Methods written by Gerhard Winkler and published by Springer. This book was released on 2012-09-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo methods commonly used....This book will be useful, especially to researchers with a strong background in probability and an interest in image analysis. The author has presented the theory with rigor...he doesn’t neglect applications, providing numerous examples of applications to illustrate the theory." -- MATHEMATICAL REVIEWS
Author : Michelle L. DePoy Smith
Publisher :
ISBN 13 :
Total Pages : 498 pages
Book Rating : 4.:/5 (53 download)
Download or read book Markov Chain Analysis and Statistical Inference for Start-up Demonstration Tests written by Michelle L. DePoy Smith and published by . This book was released on 2003 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:
