Inference in Hidden Markov Models - Image 1

Price loading...

Springer Inference in Hidden Markov Models

Name: Inference in Hidden Markov Models
Brand: Springer

A-106-016

Managers' Guides to Computing

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

Hidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more. 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, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models. This volume will suit anybody with an interest in inference for stochastic processes, and it will be useful for researchers and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The algorithmic parts of the book do not require an advanced mathematical background, while the more theoretical parts require knowledge of probability theory at the measure-theoretical level. From the reviews: "By providing an overall survey of results obtained so far in a very readable manner, and also presenting some new ideas, this well-written book will appeal to academic researchers in the field of HMMs, with PhD students working on related topics included. It will also appeal to practitioners and researchers from other fields by guiding them through the computational steps needed for making inference HMMs and/or by providing them with the relevant underlying statistical theory. In the reviewer's opinion this book will shortly become a reference work in its field." MathSciNet "This monograph is a valuable resource. It provides a good literature review, an excellent account of the state of the art research on the necessary theory and algorithms, and ample illustrations of numerous applications of HMM. It goes much beyond the earlier resources on HMM...I anticipate this work to serve well many Technometrics readers in the coming years." Haikady N. Nagaraja for Technometrics, November 2006

Product Specifications

Brand: Springer
Model: A-106-016
Format: hardcover
ASIN: 0387402640
Category: Books > Subjects > Business, Finance & Law > E-Commerce > Managers' Guides to Computing
Domain: Amazon UK
Release Date: 04 August 2005
Listed Since: 22 January 2007

Barcode

No barcode data available

Springer Inference in Hidden Markov Models

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Inference in Hidden Markov Models (Springer Series in Statistics)

Hidden Markov Models and Applications (Unsupervised and Semi-Supervised Learning)

Markov Chains: Models, Algorithms and Applications: 189 (International Series in Operations Research & Management Science, 189)

Markov Chains: Models, Algorithms and Applications: 189 (International Series in Operations Research & Management Science, 189)

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Hidden Markov Models in Finance: Further Developments and Applications, Volume II: 209 (International Series in Operations Research & Management Science, 209)

Bayesian Inference of State Space Models: Kalman Filtering and Beyond (Springer Texts in Statistics)

Hidden Markov Models: Applications to Financial Economics: 40 (Advanced Studies in Theoretical and Applied Econometrics, 40)

Hidden Markov Models: Theory and Implementation using MATLAB®

Theory of Statistical Inference (Chapman & Hall/CRC Texts in Statistical Science)

Models for Probability and Statistical Inference: Theory and Applications (Wiley Series in Probability and Statistics)

Elements of Applied Stochastic Processes: 378 (Wiley Series in Probability and Statistics)

Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics)

Springer Inference for Functional Data with Applications Book

Statistics in the Health Sciences: Theory, Applications, and Computing

Bayesian Inference in the Social Sciences

CRC Press Probability and Statistical Inference Textbook

Theory of Statistical Inference (Chapman & Hall/CRC Texts in Statistical Science)

Hierarchical Linear Models: Applications and Data Analysis Methods: 1 (Advanced Quantitative Techniques in the Social Sciences)

Introduction to Statistical Modelling and Inference

Hidden Markov Models: Theory and Implementation using MATLAB®

Bayesian Inference for Stochastic Processes

Markov Chains (Springer Series in Operations Research and Financial Engineering)

CRC Press Linear Models and Relevant Distributions Text