Name: Accelerated Life Models: Modeling and Statistical Analysis
Price: 11905.00 TWD
Availability: InStock
Author: Bagdonavicius, Vilijandas ; Nikulin, Mikhail
ISBN: 9781584881865

portada Accelerated Life Models: Modeling and Statistical Analysis

Accelerated Life Models: Modeling and Statistical Analysis

Type

Physical Book

Author

Vilijandas Bagdonavicius

Mikhail Nikulin

Publisher

CRC Press

Year

2001

Language

English

Pages

360

Format

Hardcover

Dimensions

24.1 x 15.4 x 2.5 cm

Weight

0.63 kg.

ISBN

1584881860

ISBN13

9781584881865

Synopsis "Accelerated Life Models: Modeling and Statistical Analysis"

The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models. In a unified, systematic presentation, this monograph fully details those models and explores areas of accelerated life testing usually only touched upon in the literature. Accelerated Life Models: Modeling and Statistical Analysis presents models, methods of data collection, and statistical analysis for failure-time regression data in accelerated life testing and for degradation data with explanatory variables. In addition to the classical results, the authors devote considerable attention to models with time-varying explanatory variables and to methods of semiparametric estimation. They also examine the simultaneous analysis of degradation and failure-time data when the intensities of failure in different modes depend on the level of degradation and the values of explanatory variables. The authors avoid technical details by explaining the ideas and referring to resources where thorough analysis can be found. Whether used for teaching, research or general reference, Accelerated Life Models: Modeling and Statistical Analysis provides new and known models and modern methods of accelerated life data analysis.

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Accelerated Life Models: Modeling and Statistical Analysis - Bagdonavicius, Vilijandas ; Nikulin, Mikhail

Synopsis "Accelerated Life Models: Modeling and Statistical Analysis"

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