Dependence Among Order Statistics for time-transformed exponential models

Authors

Subhash C. Kochar, Portland State UniversityFollow
Fabio Spizzichino, University of Rome

Published In

Probability in the Engineering and Informational Sciences

Document Type

Article

Publication Date

11-2023

Subjects

Statistics--Methodology

Abstract

Let X₁, ..., X_n 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, X_i:n denote the corresponding ith-order statistic. We consider the problem of comparing the strength of dependence between any pair of X_i’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.

Locate the Document

https://doi.org/10.1017/S0269964823000190

DOI

10.1017/S0269964823000190

Persistent Identifier

https://archives.pdx.edu/ds/psu/40960

Citation Details

Kochar, S., & Spizzichino, F. L. (2023). Dependence among order statistics for time-transformed exponential models. Probability in the Engineering and Informational Sciences, 1-16.