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Author : Ramanpillai Krishna Pillai
Publisher :
ISBN 13 :
Total Pages : 58 pages
Book Rating : 4.:/5 (89 download)
Download or read book Some Aspects of Statistical Inference for M-th Order Markov Processes written by Ramanpillai Krishna Pillai and published by . This book was released on 1963 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : RAMANPILLAI KRISHNA PILLAI
Publisher :
ISBN 13 :
Total Pages : 136 pages
Book Rating : 4.3/5 (91 download)
Download or read book SOME ASPECTS OF STATISTICAL INFERENCE FOR M-TH ORDER MARKOV PROCESSES.. written by RAMANPILLAI KRISHNA PILLAI and published by . This book was released on 1963 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 : 306 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 306 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 :
Publisher :
ISBN 13 :
Total Pages : 240 pages
Book Rating : 4.:/5 (933 download)
Download or read book Some Aspects of Statistical Inference in Markov Chains written by and published by . This book was released on 1976 with total page 240 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 : Denis Bosq
Publisher : Springer
ISBN 13 : 0792340876
Total Pages : 354 pages
Book Rating : 4.7/5 (923 download)
Download or read book A Course in Stochastic Processes written by Denis Bosq and published by Springer. This book was released on 1996-06-30 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is an Elementary Introduction to Stochastic Processes in discrete and continuous time with an initiation of the statistical inference. The material is standard and classical for a first course in Stochastic Processes at the senior/graduate level (lessons 1-12). To provide students with a view of statistics of stochastic processes, three lessons (13-15) were added. These lessons can be either optional or serve as an introduction to statistical inference with dependent observations. Several points of this text need to be elaborated, (1) The pedagogy is somewhat obvious. Since this text is designed for a one semester course, each lesson can be covered in one week or so. Having in mind a mixed audience of students from different departments (Math ematics, Statistics, Economics, Engineering, etc.) we have presented the material in each lesson in the most simple way, with emphasis on moti vation of concepts, aspects of applications and computational procedures. Basically, we try to explain to beginners questions such as "What is the topic in this lesson?" "Why this topic?", "How to study this topic math ematically?". The exercises at the end of each lesson will deepen the stu dents' understanding of the material, and test their ability to carry out basic computations. Exercises with an asterisk are optional (difficult) and might not be suitable for homework, but should provide food for thought.
Author : A. T. Bharucha-Reid
Publisher : Courier Corporation
ISBN 13 : 0486150356
Total Pages : 485 pages
Book Rating : 4.4/5 (861 download)
Download or read book Elements of the Theory of Markov Processes and Their Applications written by A. T. Bharucha-Reid and published by Courier Corporation. This book was released on 2012-04-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate-level text and reference in probability, with numerous applications to several fields of science, presents nonmeasure-theoretic introduction to theory of Markov processes. The work also covers mathematical models based on the theory, employed in various applied fields. Prerequisites are a knowledge of elementary probability theory, mathematical statistics, and analysis. Appendixes. Bibliographies. 1960 edition.
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 : Walter F. Johnson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (959 download)
Download or read book Statistical Inference for Markov Processes written by Walter F. Johnson and published by . This book was released on 1961 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Patrick Billingsley
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (477 download)
Download or read book Statistical Inference for Markov Processes, Reprinted written by Patrick Billingsley and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dani Gamerman
Publisher : CRC Press
ISBN 13 : 9781584885870
Total Pages : 352 pages
Book Rating : 4.8/5 (858 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 352 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 Simulation for Bayesian Inference, Second Edition presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. The second edition includes access to an internet site that provides the code, written in R and WinBUGS, used in many of the previously existing and new examples and exercises. More importantly, the self-explanatory nature of the codes will enable modification of the inputs to the codes and variation on many directions will be available for further exploration. Major changes from the previous edition: · More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms · Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection · Discussion of computation using both R and WinBUGS · Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web · Sections on spatial models and model adequacy The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses.
Author : Dwight Brandon Brock
Publisher :
ISBN 13 :
Total Pages : 128 pages
Book Rating : 4.:/5 (141 download)
Download or read book Statistical Inference for Markov Renewal Processes written by Dwight Brandon Brock and published by . This book was released on 1971 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Markov Renewal Process is one which records at each time t the number of times a system visits each of a finite number (m) of states up to time t. The system moves from state to state according to a Markov chain, and the time required for each move (sojourn time) is a random variable whose distribution function may depend on the two states between which the move is made. In this paper the author develops a test for the goodness of fit of a hypothetical transition probability matrix for a Markov Renewal Process. The author illustrates this procedure numerically by applying it to a realization of a two-state Markov Renewal Process artificially generated on a computer. In addition, the author considers some Bayesian analysis for Markov Renewal Processes by assuming a matrix beta prior distribution for the transition probability matrix. The report also discusses a special case of this topic and gives an illustration for a two-state Markov Renewal Process. In the final chapter a summary of results is given and some possible future research proglems are indicated. (Author).
Author : Peter Olofsson
Publisher : John Wiley & Sons
ISBN 13 : 0470889748
Total Pages : 573 pages
Book Rating : 4.4/5 (78 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 2012-05-22 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 : Hans-Martin Krolzig
Publisher : Springer Science & Business Media
ISBN 13 : 364251684X
Total Pages : 369 pages
Book Rating : 4.6/5 (425 download)
Download or read book Markov-Switching Vector Autoregressions written by Hans-Martin Krolzig and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to re cent developments on the statistical analysis of multiple time series in the presence of regime shifts. Markov-switching models have become popular for modelling non-linearities and regime shifts, mainly, in univariate eco nomic time series. This study is intended to provide a systematic and operational ap proach to the econometric modelling of dynamic systems subject to shifts in regime, based on the Markov-switching vector autoregressive model. The study presents a comprehensive analysis of the theoretical properties of Markov-switching vector autoregressive processes and the related statistical methods. The statistical concepts are illustrated with applications to empirical business cyde research. This monograph is a revised version of my dissertation which has been accepted by the Economics Department of the Humboldt-University of Berlin in 1996. It con sists mainly of unpublished material which has been presented during the last years at conferences and in seminars. The major parts of this study were written while I was supported by the Deutsche Forschungsgemeinschajt (DFG), Berliner Graduier tenkolleg Angewandte Mikroökonomik and Sondeiforschungsbereich 373 at the Free University and Humboldt-University of Berlin. Work was finally completed in the project The Econometrics of Macroeconomic Forecasting founded by the Economic and Social Research Council (ESRC) at the Institute of Economies and Statistics, University of Oxford. It is a pleasure to record my thanks to these institutions for their support of my research embodied in this study.
Author : Martin A. Tanner
Publisher : Springer
ISBN 13 : 0387946888
Total Pages : 220 pages
Book Rating : 4.3/5 (879 download)
Download or read book Tools for Statistical Inference written by Martin A. Tanner and published by Springer. This book was released on 1997-08-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified introduction to a variety of computational algorithms for likelihood and Bayesian inference. This third edition expands the discussion of many of the techniques presented, and includes additional examples as well as exercise sets at the end of each chapter.
Author : Marie-colette Van Lieshout
Publisher : World Scientific
ISBN 13 : 1783262508
Total Pages : 185 pages
Book Rating : 4.7/5 (832 download)
Download or read book Markov Point Processes And Their Applications written by Marie-colette Van Lieshout and published by World Scientific. This book was released on 2000-07-12 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: These days, an increasing amount of information can be obtained in graphical forms, such as weather maps, soil samples, locations of nests in a breeding colony, microscopical slices, satellite images, radar or medical scans and X-ray techniques. “High level” image analysis is concerned with the global interpretation of images, attempting to reduce it to a compact description of the salient features of the scene.This book takes a stochastic approach. It studies Markov object processes, showing that they form a flexible class of models for a range of problems involving the interpretation of spatial data. Applications can be found in statistical physics (under the name of “Gibbs processes”), environmental mapping of diseases, forestry, identification of ore structure in materials science, signal analysis, object recognition, robot vision, and interpretation of images from medical scans or confocal microscopy.
