• Home
  • Science General
  • Advances in Degradation Modeling: Applications to by William Q. Meeker (auth.), M.S. Nikulin, Nikolaos Limnios,

Advances in Degradation Modeling: Applications to by William Q. Meeker (auth.), M.S. Nikulin, Nikolaos Limnios,

By William Q. Meeker (auth.), M.S. Nikulin, Nikolaos Limnios, N. Balakrishnan, Waltraud Kahle, Catherine Huber-Carol (eds.)

This volume—dedicated to William Q. Meeker at the social gathering of his 60th birthday—is a suite of invited chapters masking contemporary advances in sped up lifestyles trying out and degradation versions. The ebook covers a variety of functions to components reminiscent of reliability, quality controls, the well-being sciences, economics, and finance.

Specific themes coated include:

* sped up trying out and inference

* Step-stress checking out and inference

* Nonparametric inference

* version validity in speeded up testing

* the purpose technique approach

* Bootstrap equipment in degradation analysis

* particular inferential equipment in reliability

* Dynamic perturbed systems

* Degradation versions in statistics

Advances in Degradation Modeling is a wonderful reference for researchers and practitioners in utilized likelihood and information, commercial statistics, the health and wellbeing sciences, quality controls, economics, and finance.

Show description

Read or Download Advances in Degradation Modeling: Applications to Reliability, Survival Analysis, and Finance PDF

Best science (general) books

Extra resources for Advances in Degradation Modeling: Applications to Reliability, Survival Analysis, and Finance

Example text

Asymptotic variances of parameters (two failure modes) . . . . 2)) . . . . . . . . . . . . . . . 2)) . . . . . . . . . . . . . . . Mean-squared errors of maximum likelihood estimators in 1000 simulation runs . . . . . . . . . . . . . . . . . . . . . . Pseudo failure distances . . . . . . . . . . . . . . . . . . Interval and point estimates obtained by each method . . . .

De N. S. ua Takashi Hara Department of Systems Engineering University of Electro-Communications 1-5-1 Chofugaoka, Chofu Tokyo 182-8585 Japan D. de N. fr M. com I. Masiulaityte˙ Vilnius University Vilnius, Lithuania Md. Mesbahul Alam Department of Systems Engineering University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo 182-8585, Japan William Q. edu Narges Nazeri Rad University of Tehran Department of Mathematics, Statistics, and Computer Sciences Tehran, Iran XXXI Wayne B. S. fr Nazanin Nooraee University of Tehran Department of Mathematics Statistics and Computer Sciences Tehran, Iran Francis G.

Comparison of the parametric and nonparametric (Kaplan–Meier) estimates of RT (t) at each evaluation point . . . . . . . . . . 50 ) and confidence intervals obtained by each method of degradation data analysis (“classical” inference). Weibull distribution . . . . . . . . . . . . . . . . . . . . 50 ) and confidence intervals obtained by each method of degradation data analysis (“classical” inference). Lognormal distribution . . . . . . . . .

Download PDF sample

Rated 4.06 of 5 – based on 38 votes