Bivariate dependence, stochastic orders and conditional tails of the recurrence times in a renewal process

The structure of dependence between the forward and the backward recurrence times in a renewal process is considered. Monotonicity properties, as a function of time, for the tail of the bivariate distribution for the recurrence times are discussed, as well as their link with aging properties of the interarrival distribution F. A necessary and sufficient condition for the renewal function to be concave is also obtained. Finally, some properties of the conditional tail for one of the two recurrence times, given some information on the other, are studied. The results are illustrated by some numerical examples.

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Publication Details

Journal
Modern Stochastics Theory and Applications
Published
2024-11-08
DOI
https://doi.org/10.15559/24-vmsta266
Primary Topic
Probability and Risk Models
Type
article
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article

Bivariate dependence, stochastic orders and conditional tails of the recurrence times in a renewal process

Sotirios Losidis, Georgios Psarrakos, Konstadinos Politis
Modern Stochastics Theory and Applications
Probability and Risk Models
article

Bivariate dependence, stochastic orders and conditional tails of the recurrence times in a renewal process

Sotirios Losidis, Georgios Psarrakos, Konstadinos Politis
article en

Abstract

The structure of dependence between the forward and the backward recurrence times in a renewal process is considered. Monotonicity properties, as a function of time, for the tail of the bivariate distribution for the recurrence times are discussed, as well as their link with aging properties of the interarrival distribution F. A necessary and sufficient condition for the renewal function to be concave is also obtained. Finally, some properties of the conditional tail for one of the two recurrence times, given some information on the other, are studied. The results are illustrated by some numerical examples.

Modern Stochastics Theory and Applications
University of Piraeus (GR)
Openalex Percentile: Top 76%
Probability and Risk Models
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