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Statistical Models and Methods for Biomedical and Technical Systems (Statistics for Industry and Technology)

Statistical Models and Methods for Biomedical and Technical Systems (Statistics for Industry and Technology)
Creators: Filia Vonta, Mikhail Nikulin, Nikolaos Limnios, Catherine Huber-carol
Publisher: Birkhaeuser Boston
Category: Book

Buy New: $139.00



Sales Rank: 1290475

Media: Hardcover
Edition: 1
Number Of Items: 1
Pages: 500

ISBN: 0817644644
Dewey Decimal Number: 570
EAN: 9780817644642
ASIN: 0817644644

Publication Date: July 4, 2008  (New: This Week)
Shipping: Eligible for Super Saver Shipping
Availability: Not yet published

Accessories:

  • Statistical Monitoring of Clinical Trials: A Unified Approach (Statistics for Biology and Health)
  • Fundamentals of Clinical Trials
  • Analysis of Phylogenetics and Evolution with R (Use R)

Editorial Reviews:

Product Description

An outgrowth of the "International Conference on Statistical Models for Biomedical and Technical Systems," this book is comprised of contributions from renowned experts, demonstrating the significance of current research on theory, methods, and applications of the field. The contributions, which deal with the mathematical aspects of survival analysis and reliability as well as other topics, are a careful selection of invited and contributed chapters, reflecting recent developments in the following areas:

* Applications in epidemiology

* Estimation and testing for stochastic processes

* Generalizations of the Cox regression model

* Probabilistic and statistical models and methods in reliability

* Semi-parametric inference in survival analysis

* Models and methods in survival analysis, longevity, aging, and degradation

* Nonparametric estimation a Goodness-of-fit tests

* Accelerated life models

* Quality of life

* Analysis of censored data

* Adaptive and repeated measurements designs

* Measures of divergence, model selection, and survival models

* New statistical challenges in genomics

The book will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering. Practitioners and researchers in academia will gain insight and new ideas for exploring this fertile area of research.



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