Titlebook: Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Qualit; N. Balakrishnan,M. S. Nikulin,N. Lim

angina-pectoris

Zhezhen Jin,Zhiliang Yinght man meist nur sehr wenig Vorkenntnisse; oftmals genügen schon die aus der Schule bekannten Rechenregeln. Zus?tzlich werden jedoch einige grundlegende Fakten über Zahlen und Teilbarkeit ben?tigt, die wir im n?chsten Abschnitt kurz vorstellen.

Individual

Book 2004ntained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, s

無關(guān)緊要

Estimation in Partly Parametric Additive Cox Modelsscuss here the estimation of interesting parameters. We represent the maximum likelihood approach and extend the results of (.) from linear to nonlinear parameters. Then we investigate the least squares estimation and formulate conditions for the a.s. boundedness and consistency of these estimators.

逢迎春日

Nonparametric Maximum Likelihood Estimation in the Proportional Hazards Model with Covariate Measurement Error values are frequently subject to measurement error. Substituting mismeasured values for the true covariates in the PH model leads to biased estimation. (.) have proposed to base estimation for the PH model with covariate measurement error on a joint likelihood for survival and the covariate. The au

遺產(chǎn)

BRACE

On a Degradation-Failure Model for Repairable Itemsnt. An item is regarded as failed when degradation reaches a critical threshold level or when a censoring traumatic event occurs. Degradation is modelled by a process with stationary independent increments and is related to external covariates through a random time scale. Traumatic events occur due

intolerance

Comparison of Parametric and Semiparametric Estimates in a Degradation Model with Covariates and Traumatic Censoringe most important models include finite state Markov chains or semiMarkov processes [for which some transitions mean deteriorating or improving and where the states reflect the levels of degradation, see (.)] or models describing the degradation by the evolution (often increasing) of a random functio

ineluctable

Accelerated Life Testing, Fuzzy Information and Generalized Probabilityfe time data are always more or less non-precise. This kind of data uncertainty is called fuzziness. The best up to date mathematical description of non-precise life times is by so-called fuzzy numbers. In ALT the fuzziness is increased by the models used to transform life times under high stress le

證實

Asymptotic Theory in Rank Estimation for AFT Model Under Fixed Censorship.)]. A key assumption in establishing the asymptotic normality for the rank estimator is that, conditional on covariates, the censoring time has a density function. This assumption may be violated in many situations. It may also be non-intrinsic in that the limiting variance formula does not involve

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