Download e-book for iPad: 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.)

ISBN-10: 0817649239

ISBN-13: 9780817649234

This volume—dedicated to William Q. Meeker at the party of his 60th birthday—is a set of invited chapters overlaying contemporary advances in sped up existence checking out and degradation types. The e-book covers a variety of functions to components corresponding to reliability, quality controls, the future health sciences, economics, and finance.

Specific themes lined include:

* speeded up checking out and inference

* Step-stress checking out and inference

* Nonparametric inference

* version validity in speeded up testing

* the purpose approach approach

* Bootstrap equipment in degradation analysis

* distinctive inferential tools in reliability

* Dynamic perturbed systems

* Degradation versions in statistics

Advances in Degradation Modeling is a wonderful reference for researchers and practitioners in utilized chance and records, business data, the well-being sciences, quality controls, economics, and finance.

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

Example text

The hazard function Λ1 (t; 15, 10, 15) with μ = 2 and λ = 1 . . . Reliability function R2 (t; τ1 , τ2 , β) with K = 2 . . . . . . . . . The reliability function R1∗ (t; k, β0 , β1 ) . . . . . . . . . . . . The reliability function Rc (t; γ0 , β0 , β1 ) . . . . . . . . . . . . The reliability function RL (t; β) . . . . . . . . . . . . . . . Wiener process degradation model . . . . . . . . . . . . . . Gamma process degradation model .

4 Estimation results . . . . . . . . . . . . . . . . . . . . . 1 Estimates and confidence intervals for the control group . . . . 2 Estimates and confidence intervals for the test group . . . . . . 3 τ1 = 100, τ2 = 150, θ1 = 1/100, θ2 = 1/50 . . . . . . . . . . 4 Known Ratio . . . . . . . . . . . . . . . . . . . . . . . 5 τ1 = 100, τ2 = 150, θ1 = 1/100, θ2 = 1/25 . . . . . . . . . . 6 Known ratio . . . . . . . . . . . .

4 Probability plots for the cancer data set with pointwise confidence intervals for failure-time cdf F assuming independent lognormal cancer deaths and Weibull other deaths. Plot (a) is for deaths due to cancer. Plot (b) is for deaths due to other causes . . . . . . . . 5 Probability plots for the cancer data set with pointwise confidence intervals for failure-time cdf F assuming independent lognormal risks. Plot (a) is for deaths due to cancer. Plot (b) is for deaths due to other causes .

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Advances in Degradation Modeling: Applications to Reliability, Survival Analysis, and Finance by William Q. Meeker (auth.), M.S. Nikulin, Nikolaos Limnios, N. Balakrishnan, Waltraud Kahle, Catherine Huber-Carol (eds.)


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