Diagnostics of prior-data agreement in applied Bayesian analysis

This article focused on the definition and the study of a binary Bayesian criterion which measures a statistical agreement between a subjective prior and data information. The setting of this work is concrete Bayesian studies. It is an alternative and a complementary tool to the method recently proposed by Evans and Moshonov, [M. Evans and H. Moshonov, Checking for Prior-data conflict, Bayesian Anal. 1 (2006), pp. 893–914]. Both methods try to help the work of the Bayesian analyst, from preliminary to the posterior computation. Our criterion is defined as a ratio of Kullback–Leibler divergences; two of its main features are to make easy the check of a hierarchical prior and be used as a default calibration tool to obtain flat but proper priors in applications. Discrete and continuous distributions exemplify the approach and an industrial case study in reliability, involving the Weibull distribution, is highlighted.     

Critical Values for the Robust Rank-Order Test

ABSTRACT

The nonparametric Wilcoxon–Mann–Whitney test is commonly used by practitioners for detecting differences in location (mean, median) between two samples. Earlier work has shown this test to have a number of disadvantages, most of which are remedied by use of the alternative robust rank-order test. Use of the robust rank-order test has been limited, perhaps partly because exact critical values have up to now been available for only a small number of sample-size values, and not for all of the commonly used levels of significance. This article expands what is known about the distribution of the robust rank-order test statistic; critical values are given for more sample sizes and for more levels of significance.     

Aspects of Dependence in Cuadras–Auge Family

In this article, we study the dependence structure of Cuadras–Auge (C–A) family of bivariate distributions. We also obtain some association measures and two local dependence functions for this family. In addition, we compare expectation of local dependence function and Pearson's rho via numerical study.     

Large Sample Properties of ML Estimator of the Parameters of Multivariate O–U Random Fields

Computer modeling is having a profound effect on scientific research, replacing direct physical experimentation by computer simulation of complex models. In this research, the computer output, X(t), is assumed to be a multivariate, three-dimensional (time) Ornstein-Uhlenbeck (O–U) process with parametric covariance function. It is shown that the ML estimates of the parameters are strongly consistent and asymptotically normal when the observations are taken from a complete lattice, not necessarily equally spaced.     

Analysis of incomplete data in the presence of dependent competing risks from Marshall–Olkin bivariate Weibull distribution under progressive hybrid censoring

This article considers the statistical analysis of dependent competing risks model with incomplete data under Type-I progressive hybrid censored condition using a Marshall–Olkin bivariate Weibull distribution. Based on the expectation maximum algorithm, maximum likelihood estimators for the unknown parameters are obtained, and the missing information principle is used to obtain the observed information matrix. As the maximum likelihood approach may fail when the available information is insufficient, Bayesian approach incorporated with auxiliary variables is developed for estimating the parameters of the model, and Monte Carlo method is employed to construct the highest posterior density credible intervals. The proposed method is illustrated through a numerical example under different progressive censoring schemes and masking probabilities. Finally, a real data set is analyzed for illustrative purposes.     

On a general mixed priority queue with server discretion

We consider a single-server queueing system which attends to N priority classes that are classified into two distinct types: (i) urgent: classes which have preemptive resume priority over at least one lower priority class, and (ii) non-urgent: classes which only have non-preemptive priority among lower priority classes. While urgent customers have preemptive priority, the ultimate decision on whether to interrupt a current service is based on certain discretionary rules. An accumulating prioritization is also incorporated. The marginal waiting time distributions are obtained and numerical examples comparing the new model to other similar priority queueing systems are provided.     

General analysis of systems in which a 2-unit system is a sub-system

In this paper we consider a system which has three subsystems A, B and C. A and B are one unit systems and two unit systems respectively, and C is exposed to a damage process. The units of B have exponential life times. In model 1, A has a general life time and the damage process of C is Poisson and in model 2, A has an exponential life time and C is exposed to a renewal damage process. Introducing a repair facility which repairs all the failures one by one, this paper presents the joint Laplace-Stieltjes transforms of the ur> and down times. Marginal down time distributions an- calculated whon there exists a repair facility vor every damage.     

Acceptance Sampling Plans from Truncated Life Tests Based on the Generalized Birnbaum–Saunders Distribution

In this article, we develop acceptance sampling plans when the life test is truncated at a pre-fixed time. The minimum sample size necessary to ensure the specified median life is obtained by assuming that the lifetimes of the test units follow a generalized Birnbaum–Saunders distribution. The operating characteristic values of the sampling plans as well as producer's risk are presented. Two examples are also given to illustrate the procedure developed here, with one of them being based on a real data from software reliability.     

Bhattacharyya and Kshirsagar Bounds in Generalized Gamma Distribution

In this article, we consider the exact computation of the famous halfspace depth (HD) and regression depth (RD) from the view of cutting a convex cone with hyperplanes. Two new algorithms are proposed for computing these two notions of depth. The first one is relatively straightforward but quite inefficient, whereas the second one is much faster. It is noteworthy that both of them can be implemented to spaces with dimension beyond three. Some numerical examples are also provided in what follows to illustrate the performances.     

Estimation of reliability with cumulative stress and strength degradation

In many real-life scenarios, system reliability depends on dynamic stress–strength interference where strength degrades and stress accumulates concurrently over time. In this paper, we consider the problem of estimating reliability of a system under deterministic strength degradation and cumulative damage due to shocks arriving according to a point process. Maximum likelihood estimation under two different sampling plans has been considered. Large sample properties in general are discussed. The method is illustrated through simulation and real-life data analysis.