Multivariate stress-strength reliability model and its evaluation for coherent structures
Journal of Multivariate Analysis
Mixture representation for order statistics from INID progressive censoring and its applications
Journal of Multivariate Analysis
Multivariate order statistics based on dependent and nonidentically distributed random variables
Journal of Multivariate Analysis
Multivariate order statistics via multivariate concomitants
Journal of Multivariate Analysis
On multivariate order statistics. Application to ranked set sampling
Computational Statistics & Data Analysis
Distortion exponents for decode-and-forward multi-relay cooperative networks
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
On the distortion exponents of layered broadcast transmission in multi-relay cooperative networks
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
For a sequence of independent and identically distributed random vectors X"i=(X"i^1,X"i^2,...,X"i^p), i=1,2,...,n, we consider the conditional ordering of these random vectors with respect to the magnitudes of N(X"i),i=1,2,...,n, where N is a p-variate continuous function defined on the support set of X"1 and satisfying certain regularity conditions. We also consider the Progressive Type II right censoring for multivariate observations using conditional ordering. The need for the conditional ordering of random vectors exists for example, in reliability analysis when a system has n independent components each consisting of p arbitrarily dependent and parallel connected elements. Let the vector of life lengths for the ith component of the system be X"i=(X"i^1,X"i^2,...,X"i^p),i=1,2,...,n, where X"i^j denotes the life length of the jth element of the ith component. Then the first failure in the system occurs at time minmax(X"1^1,X"1^2,...,X"1^p),max(X"2^1,X"2^2,...,X"2^p),...,max(X"n^1,X"n^2,...,X"n^p), and for this case N(X"i)=max(X"i^1,X"i^2,...,X"i^p). In this paper we introduce the conditionally ordered and Progressive Type II right-censored conditionally ordered statistics for multivariate observations and to study their distributional properties.