Characterizations of the General Multivariate Weibull Distributions

For studying and modeling the time to failure of a system or component, many reliability practitioners used the hazard rate and its monotone behaviors. However, nowadays, there are two problems. First, the modern components have high reliability and, second, their distributions are usually have non monotone hazard rate, such as, the truncated normal, Burr XII, and inverse Gaussian distributions. So, modeling these data based on the hazard rate models seems to be too stringent. Zimmer et al. (1998 Zimmer , W. J. , Wang , Y. , Pathak , P. K. ( 1998 ). Log-odds rate and monotone log-odds rate distributions . J. Qual. Technol. 30 ( 4 ): 376 – 385 .[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and Wang et al. (2003 Wang , Y. , Hossain , A. M. , Zimmer , W. J. ( 2003 ). Monotone log-odds rate distributions in reliability analysis . Commun. Statist. Theor. Meth. 32 ( 11 ): 2227 – 2244 .[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar], 2008 Wang , Y. , Hossain , A. M. , Zimmer , W. J. ( 2008 ). Useful properties of the three-parameter Burr XII distribution. In: Ahsanullah M., Applied Statistics Research Progress. pp. 11–20 . [Google Scholar]) introduced and studied a new time to failure model in continuous distributions based on log-odds rate (LOR) which is comparable to the model based on the hazard rate.

There are many components and devices in industry, that have discrete distributions with non monotone hazard rate, so, in this article, we introduce the discrete log-odds rate which is different from its analog in continuous case. Also, an alternative discrete reversed hazard rate which we called it the second reversed rate of failure in discrete times is also defined here. It is shown that the failure time distributions can be characterized by the discrete LOR. Moreover, we show that the discrete logistic and log logistics distributions have property of a constant discrete LOR with respect to t and ln t, respectively. Furthermore, properties of some distributions with monotone discrete LOR, such as the discrete Burr XII, discrete Weibull, and discrete truncated normal are obtained.     

Methods for Bivariate Survival Data with Mismeasured Covariates Under an Accelerated Failure Time Model

Accelerated failure time models are useful in survival data analysis, but such models have received little attention in the context of measurement error. In this paper we discuss an accelerated failure time model for bivariate survival data with covariates subject to measurement error. In particular, methods based on the marginal and joint models are considered. Consistency and efficiency of the resultant estimators are investigated. Simulation studies are carried out to evaluate the performance of the estimators as well as the impact of ignoring the measurement error of covariates. As an illustration we apply the proposed methods to analyze a data set arising from the Busselton Health Study (Knuiman et al., 1994 Knuiman , M. W. , Cullent , K. J. , Bulsara , M. K. , Welborn , T. A. , Hobbs , M. S. T. ( 1994 ). Mortality trends, 1965 to 1989, in Busselton, the site of repeated health surveys and interventions . Austral. J. Public Health 18 : 129 – 135 . [CSA] [Crossref], [PubMed] , [Google Scholar]).     

Natural Exponential Families and Generalized Hypergeometric Measures

Let ν be a positive Borel measure on ?ⁿ and _pF_q(a₁,…, a_p; b₁,…, b_q; s) be a generalized hypergeometric series. We define a generalized hypergeometric measure, μ_p,q := _pF_q(a₁,…, a_p; b₁,…, b_q;ν), as a series of convolution powers of the measure ν, and we investigate classes of probability distributions which are expressible as such a measure. We show that the Kemp (1968 Kemp , A. W. ( 1968 ). A wide class of discrete distributions and the associated differential equations . Sankhyā, Ser. A 30 : 401 – 410 . [Google Scholar]) family of distributions is an example of μ_p,q in which ν is a Dirac measure on ?. For the case in which ν is a Dirac measure on ?ⁿ, we relate μ_p,q to the diagonal natural exponential families classified by Bar-Lev et al. (1994 Bar-Lev , S. K. , Bshouty , D. , Enis , P. , Letac , G. , Lu , I. , Richards , D. ( 1994 ). The diagonal natural exponential families on ? ⁿ and their classification . J. Theoret. Probab. 7 : 883 – 929 .[Crossref] , [Google Scholar]). For p < q, we show that certain measures μ_p,q can be expressed as the convolution of a sequence of independent multi-dimensional Bernoulli trials. For p = q, q + 1, we show that the measures μ_p,q are mixture measures with the Dufresne and Poisson-stopped-sum probability distributions as their mixing measures.     

On Simultaneous Estimation of the Number of Signals and Frequencies of Multiple Sinusoids When Some Observations Are Missing

In an earlier article (Bai et al., 1999 Bai , Z. D. , Rao , C. R. , Wu , Y. H. , Zen , M. M. , Zhao , L. C. ( 1999 ). The simultaneous estimation of the number of signals and frequencies of multiple sinusods when some observations are missing: I. Asymptotics . Proc. Natl. Acad. Sci. 96 : 11,106 – 11,110 . [CSA] [Crossref], [Web of Science ®] , [Google Scholar]), the problem of simultaneous estimation of the number of signals and frequencies of multiple sinusoids is considered in the case that some observations are missing. The number of signals is estimated with an information theoretic criterion and the frequencies are estimated with eigenvariation linear prediction. Asymptotic properties of the procedure are investigated but the Monte Carlo simulation is not performed. In this article, a slightly different but scale invariant criterion for detection is proposed and the estimation of frequencies remains the same. Asymptotic properties of this new procedure are provided. Monte Carlo Simulation for both procedures is carried out. Furthermore, comparison on the real signals is also given.     

Comparison of Frailty Models for Acute Leukemia Data under Gompertz Baseline Distribution

In this article, we consider two different shared frailty regression models under the assumption of Gompertz as baseline distribution. Mostly assumption of gamma distribution is considered for frailty distribution. To compare the results with gamma frailty model, we consider the inverse Gaussian shared frailty model also. We compare these two models to a real life bivariate survival data set of acute leukemia remission times (Freireich et al., 1963 Freireich, E.J., Gehan, E., Frei, E., Schroeder, L.R., Wolman, I.J., Anbari, R., Burgert, E.O., Mills, S.D., Pinkel, D., Selawry, O.S., Moon, J.H., Gendel, B.R., Spurr, C.L., Storrs, R., Haurani, F., Hoogstraten, B., Lee, S. (1963). The effect of 6-mercaptopurine on the duration of steroid-induced remissions in acute leukemia: a model for evaluation of other potentially useful therapy. Blood 21:699–716.[Web of Science ®] , [Google Scholar]). Analysis is performed using Markov Chain Monte Carlo methods. Model comparison is made using Bayesian model selection criterion and a well-fitted model is suggested for the acute leukemia data.