Approximation of reliability for a large system with non-markovian repair-times
Approximation of Reliability for a large system with non-markovian repair-times
Consider a system of many components with constant failure rate and general repair rate. When all components are reliable and easily reparable, the reliability of the system can be evaluated from the probability q of failure before restoration. In [14], authors give an asymptotic approximation by monotone sequences. In the same framework, we propose, here, a bounding for q and apply it in the ageing property case.
Aspects of analysis of multivariate failure time data.
Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have depending event times; or more complicated multistate processes where individuals may move among a number of discrete states over...
Assessing influence in survival data with a cured fraction and covariates.
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to...
Asymptotic expansions of functions of statistics
Bayes estimation of the reliability function and hazard rate of a Weibull failure time distribution.
Given the recorded life times from a Weibull distribution, Bayes estimates of the reliability function and hazard rate are obtained using the posterior distributions and some recent results on Bayesian approximations due to Lindley (1980). Based on a Monte Carlo study, these estimates are compared with their maximum likelihood counterparts.
Bayesian approach for joint longitudinal and time-to-event data with survival fraction.
Bayesian estimation of the 3-parameter inverse Gaussian distribution.
The three-parameter inverse Gaussian distribution is used as an alternative model for the three parameter lognormal, gamma and Weibull distributions for reliability problems. In this paper Bayes estimates of the parameters and reliability function of a three parameter inverse Gaussian distribution are obtained. Posterior variance estimates are compared with the variance of their maximum likelihood counterparts. Numerical examples are given.
Bayesian inference and optimal release times. For two software failure models
We carry out Bayesian inference for the Jelinski-Moranda and Littlewood software failure models given a sample of failure times. Furthermore, we illustrate how to assess the optimal length of an additional pre-release testing period under each of these models. Modern Bayesian computational methods are used to estimate the posterior expected utility of testing for and additional time.
Bayesian nonparametric estimation of hazard rate in monotone Aalen model
This text describes a method of estimating the hazard rate of survival data following monotone Aalen regression model. The proposed approach is based on techniques which were introduced by Arjas and Gasbarra [4]. The unknown functional parameters are assumed to be a priori piecewise constant on intervals of varying count and size. The estimates are obtained with the aid of the Gibbs sampler and its variants. The performance of the method is explored by simulations. The results indicate that the...
Bayesian Prediction of Weibull Distribution Based on Fixed and Random Sample Size
2000 Mathematics Subject Classification: 62E16, 65C05, 65C20.We consider the problem of predictive interval for future observations from Weibull distribution. We consider two cases they are: (i) fixed sample size (FSS), (ii) random sample size (RSS). Further, we derive the predictive function for both FSS and RSS in closed forms. Next, the upper and lower 1%, 2.5%, 5% and 10% critical points for the predictive functions are calculated. To show the usefulness of our results, we present some simulation...
Bayesian reference analysis for proportional hazards model of random censorship with Weibull distribution
This article deals with the objective Bayesian analysis of random censorship model with informative censoring using Weibull distribution. The objective Bayesian analysis has a long history from Bayes and Laplace through Jeffreys and is reaching the level of sophistication gradually. The reference prior method of Bernardo is a nice attempt in this direction. The reference prior method is based on the Kullback-Leibler divergence between the prior and the corresponding posterior distribution and easy...
Bayesian reliability analysis when multiple early failures may be present.
This paper discusses the Bayesian reliability analysis for an exponential failure mode on the basis of some ordered observations when the first p observations may represent early failures or outliers. The Bayes estimators of the mean life and reliability are obtained for the underlying parametric model referred to as the SB(p) model under the assumption of the squared error loss function, the inverted gamma prior for scale parameter and a generalized uniform prior for the nuisance parameter.
Bayesian Shrinkage Estimation of Reliability in the Exponential Distribution
Bayesian survival analysis based on the Rayleigh model.
In this paper, the Bayesian analysis of the survival data arising from a Rayleigh model is carried out under the assumption that the clinical study based on n patients is terminated at the dth death, for some preassigned d (0 < d ≤ n), resulting in the survival times t1 ≤ t2 ≤ ... ≤ td, and (n - d) survivors. For the prior knowledge about the Rayleigh parameter, the gamma density, the inverted gamma density, and the beta density of the second kind are respectively assumed, and for each of...
Behaviour of higher-order approximations of the tests in the single parameter Cox proportional hazards model
Survival analysis is applied in a wide range of sectors (medicine, economy, etc.), and its main idea is based on evaluating the time until the occurrence of an event of interest. The effect of some particular covariates on survival time is usually described by the Cox proportional hazards model and the statistical significance of the impact of covariates is verified by the likelihood ratio test, the Wald test, or the score test. In addition to standard tests, appropriate higher-order approximations...
Bias correction on censored least squares regression models
This paper proposes a bias reduction of the coefficients' estimator for linear regression models when observations are randomly censored and the error distribution is unknown. The proposed bias correction is applied to the weighted least squares estimator proposed by Stute [28] [W. Stute: Consistent estimation under random censorship when covariables are present. J. Multivariate Anal. 45 (1993), 89-103.], and it is based on model-based bootstrap resampling techniques that also allow us to work with...
Bivariate gamma distribution as a life test model
The bivariate gamma distribution is taken as a life test model to analyse a series system with two dependent components and . First, the distribution of a function of and , that is, minimum , is obtained. Next, the reliability of the component system is evaluated and tabulated for various values of the parameters. Estimates of the parameters are also obtained by using Bayesian approach. Finally, a table of the mean and variance of minimum for various values of the parameters involved is...
Bounds for the mean square error of reliability estimation from gamma distribution in presence of an outlier observation.
Cálculo de la distribución del tiempo de vida de componentes mediante autopsia en sistemas binarios aditivos, serie-paralelo y paralelo-serie.
En este artículo se estudia el problema de determinar la función de distribución del tiempo de vida de las componentes de un sistema binario, a partir del conocimiento de las leyes que rigen el funcionamiento del sistema y del conjunto de componentes que causa su fallo (obtenida mediante autopsia del sistema en el momento de su deterioro).Se presentan los resultados de Meilijson (1981) y Nowik (1990) que proponen un sistema de ecuaciones implícito para obtener estas distribuciones. Sin embargo,...