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Download Accelerated Life Models: Modeling and Statistical Analysis djvu

by Vilijandas Bagdonavicius,Mikhail Nikulin

Author: Vilijandas Bagdonavicius,Mikhail Nikulin
Subcategory: Management & Leadership
Language: English
Publisher: Chapman and Hall/CRC; 1 edition (November 28, 2001)
Pages: 360 pages
Category: Perfomance
Rating: 4.6
Other formats: txt doc mbr azw

Vilijandas Bagdonavicius, Mikhail Nikulin. The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models.

Vilijandas Bagdonavicius, Mikhail Nikulin. 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.

Vilijandas B. Bagdonavicius. Accelerated Life Models : Modeling and Statistical Analysis, V. Bagdonavicius, M. Nikulin. Goodness-of-fit tests for accelerated life models and generalizing or alternative to the additive risk model are proposed. On goodness-of-fit for the linear transformation and frailty models. The most of papers on Accelerated Life Testing consider parametric models with Weibull, log-normal, log-logistic or ex- ponential lifetime distributions View.

Accelerated Life Models:. has been added to your Cart. An ex-library book and may have standard library stamps and/or stickers. Accelerated Life Models (ALT). Statistical Analysis of ALT Data Using Additive Accumulation of Damages (ADD). Statistical Analysis of ALT Data Using CHSH Models. Statistical Analysis of ALT Data Using GPH, GH, and GA. Models. ALT When a Process of Production is Unstable.

Accelerated Life Models: Modeling and Statistical Analysis. Vilijandas Bagdonavicius, Mikhail Nikulin. Statistical Modeling in Survival Analysis and Its Influence on the Duration Analysis. Failure Time Distributions Introduction Parametric Classes of Failure Time Distributions Accelerated Life Models Introduction Generalized Sedyakin's Model Accelerated Failure Time Model Proportiona. More). Publisher Summary Survival-regression models relate lifetime distribution to the explanatory variables (covariates) and are used for the estimation of the effect of covariates on survival and fo. V Bagdonavicius, M Nikulin. Estimation in degradation models with explanatory variables. V Bagdonavicius, MS Nikulin. Chapman and Hall/CRC, 2001. Unbiased Estimators and their Applications, . : Univariate case. VG Voinov, MS Nikulin. Kluwer Academic Publishers: Dordrecht, 1993. Unbiased Estimators and their Applications. Lifetime Data Analysis 7 (1), 85-103, 2001. Goodness-of-fit tests and model validity. C Huber-Carol, N Balakrishnan, M Nikulin, M Mesbah, (eds). Analysis of variance for functional data.

Vilijandas Bagdonavičius. In: Huber-Carol . Balakrishnan . Mesbah M. (eds) Goodness-of-Fit Tests and Model Validity. Statistics for Industry and Technology. Part of the Statistics for Industry and Technology book series (SIT). Accelerated life testing accelerated failure time (AFT) Cox model Generalized Sedyakin’s model (GS) goodness-of-fit power function proportional hazards (PH) Sedyakin’s model step-stress. Birkhäuser, Boston, MA.

Road Crash Prediction Models: Different Statistical Modeling Approaches. A Statistical Analysis of Wind Speed and Power Density Based on Weibull and Rayleigh Models of Jumla, Nepal. 72014 1 240 Downloads 2 981 Views Citations. 87026 2 354 Downloads 3 543 Views Citations.

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.