Flowgraph Models for Multistate Time-to-Event Data

Передня обкладинка
John Wiley & Sons, 19 лист. 2004 р. - 320 стор.
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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Зміст

1 Multistate Models and Flowgraph Models
1
2 Flowgraph Models
10
3 Inversion of Flowgraph Moment Generating Functions
43
4 Censored Data Histograms
71
5 Bayesian Prediction for Flowgraph Models
89
6 Computational Implementation of Flowgraph Models
129
7 SemiMarkov Processes
145
8 Incomplete Data
187
9 Flowgraph Models for Queuing Systems
206
Appendix Moment Generating Functions
247
References
251
Author Index
261
Subject Index
265
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Загальні терміни та фрази

Посилання на книгу

Advances in Survival Analysis
Narayanaswamy Balakrishnan,C.R. Rao
Обмежений попередній перегляд - 2004
Modern Statistical and Mathematical Methods in Reliability
Alyson G. Wilson
Обмежений попередній перегляд - 2005

Про автора (2004)

APARNA V. HUZURBAZAR, PhD, 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.

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