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Ahad Jamalizadeh,H. Mahmoodian,A. Pourdarvish,N. Balakrishnan 한국통계학회 2012 Journal of the Korean Statistical Society Vol.41 No.2
In this paper, by considering a (k + n)-dimensional random vector XT , YT T , X ∈ Rk and Y ∈ Rn, having a multivariate elliptical distribution, we derive the exact distribution of AX + LY (n), where A ∈ Rp×k, L ∈ Rp×n, and Y(n) = Y(1), Y(2), . . . , Y(n)T denotes the vector of order statistics from Y. Next, we discuss the distribution of aTX+bY(r), for r = 1, . . . ,n, a =(a1, . . . , ak)T ∈ Rk and b ∈ R. We show that these distributions can be expressed as mixtures of multivariate unified skew-elliptical distributions. Finally, we illustrate an application of the established results to stock fund evaluation.
Analysis of competing risks in the burr XII model in presence of progressive type-II censoring
A. Pourdarvish,R. Hashemi,J. Azar 장전수학회 2012 Proceedings of the Jangjeon mathematical society Vol.15 No.1
In reliability and survival analysis, it is quite common that the failure of any individual or any item may be attributable to more than one cause (competing risks). In this paper, we will study the competing risks in the Burr XII model in the presence of progressive type II censoring scheme. We study the model under the assumption of independent causes of failure. The maximum likelihood estimator was developed to estimate the unknown parameters. The asymptotic distribution of the maximum likelihood estimators is used to construct approximate confidence interval. We also present a simulation study to illustrate the results.