Flowgraph Models for Multistate Time to Event Data

Szerző: Aparna V. Huzurbazar

Nyelv:

Kötés: Kemény kötésű

Kiadó: John Wiley & Sons Inc

Elérhetőség: Beszállítói készleten

Küldés 9-15 napon belül

71 233 Ft

A unique introduction to the innovative methodology of statistical flowgraphs This book offers a pra...

Információk a könyvről

Szerző

Aparna V. Huzurbazar

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2004

oldal

270

EAN

9780471265146

ISBN

0471265144

Enbook ID

04889164

Kiadó

John Wiley & Sons Inc

Súly

570

Méretek

158 x 242 x 22

Teljes leírás

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.

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Flowgraph Models for Multistate Time to Event Data

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