The Stress-strength Model and Its Generalizations: Theory and Applications
This important book presents developments in a remarkable field ofinquiry in statistical/probability theory the stressOCostrengthmodel.Many papers in the field include the enigmatic words"P"("X"Y") or something similar in thetitle."
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applications approximate assume assumption asymptotic confidence interval asymptotically normal Bayes estimator Bayesian beta distribution binomial bivariate bootstrap Burr type BVED calculations Casella Chapter components confidence interval confidence intervals based defined Denote density Derive the MLE Dirichlet process Distribution Let Enis and Geisser equation estimation of P(X exact confidence intervals example exponential distribution expression follows formula function Fx(x gamma distribution given Guttman Halperin Hence hypergeometric series independent normal variables independent random variables inequality integration interval estimation Ivshin and Lumelskii Jeffreys's prior known lower confidence bound Lumelskii 1995 matching prior matrix method multivariate nonparametric Note observations obtain p-value Pareto distribution pivotal quantity posterior pdf probability problem random vector Reiser respectively ROC curve Section strength stress stress-strength models sufficient statistic system reliability T-distribution technique Theorem tion transformation two-parameter exponential UMVUE unbiased estimator unknown values Var(fi variance Weibull Weibull Distribution