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Article
Dependence Among Order Statistics for time-transformed exponential models
Probability in the Engineering and Informational Sciences
  • Subhash C. Kochar, Portland State University
  • Fabio Spizzichino, University of Rome
Document Type
Article
Publication Date
11-1-2023
Subjects
  • Statistics--Methodology
Abstract

Let X1, ..., Xn be a random vector distributed according to a time-transformed exponential model. This is a special class of exchangeable models, which, in particular, includes multivariate distributions with Schur-constant survival functions. Let for 1 i n, Xi:n denote the corresponding ith-order statistic. We consider the problem of comparing the strength of dependence between any pair of Xi’s with that of the corresponding order statistics. It is in particular proved that for m = 2, ..., n, the dependence of X2:m on X1:m is more than that of X2 on X1 according to more stochastic increasingness (positive monotone regression) order, which in turn implies that X1:m, X2:mº is more concordant than X1, X2. It will be interesting to examine whether these results can be extended to other exchangeable models.

Rights

Copyright (c) 2023 The Authors

This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI
10.1017/S0269964823000190
Persistent Identifier
https://archives.pdx.edu/ds/psu/40960
Citation Information
Kochar, S., & Spizzichino, F. L. (2023). Dependence among order statistics for time-transformed exponential models. Probability in the Engineering and Informational Sciences, 1-16.