Flowgraph Models For Mutistate ime-to-Event Data

Aparna V. Huzurbazar - Collection Wiley Series in Probability and Statistics

270 pages, parution le 16/12/2004

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Résumé

A unique introduction to the innovative methodology of statistical flowgraphs

This book offers a practical, application-based approach to flowgraph models for time-to-event data. It clearly shows how this innovative new methodology can be used to analyze data from semi-Markov processes without prior knowledge of stochastic processes-opening the door to interesting applications in survival analysis and reliability as well as stochastic processes.

Unlike other books on multistate time-to-event data, this work emphasizes reliability and not just biostatistics, illustrating each method with medical and engineering examples. It demonstrates how flowgraphs bring together applied probability techniques and combine them with data analysis and statistical methods to answer questions of practical interest. Bayesian methods of data analysis are emphasized. Coverage includes:

Clear instructions on how to model multistate time-to-event data using flowgraph models
An emphasis on computation, real data, and Bayesian methods for problem solving
Real-world examples for analyzing data from stochastic processes
The use of flowgraph models to analyze complex stochastic networks
Exercise sets to reinforce the practical approach of this volume

Flowgraph Models for Multistate Time-to-Event Data is an invaluable resource/reference for researchers in biostatistics/survival analysis, systems engineering, and in fields that use stochastic processes, including anthropology, biology, psychology, computer science, and engineering.

L'auteur - Aparna V. Huzurbazar

Aparne V. Huzurbazar is Associate Professor of Statistics at the University of New Mexico. She is the author of numerous technical articles in such areas as Bayesian statistics, survival analysis, stochastic processes, and applications to biomedical and engineering systems.

Sommaire

Preface
Multistate Models and Flowgraph Models
Flowgraph Models
Inversion of Flowgraph Moment Generating Functions
Censored Data Histograms
Bayesian Prediction for Flowgraph Models
Computation Implementation of Flowgraph Models
Semi-Markov Processes
Incomplete Data
Flowgraph Models for Queuing Systems
Appendix: Moment Generating Functions
References
Author Index
Subject Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Aparna V. Huzurbazar
Collection	Wiley Series in Probability and Statistics
Parution	16/12/2004
Nb. de pages	270
Format	16 x 24
Couverture	Relié
Poids	533g
Intérieur	Noir et Blanc
EAN13	9780471265146