Extropy: Dynamic cumulative past and residual inaccuracy measures with applications

In comparison to PDF-based measures which provided by extropy, the CDF-based measures of cumulative residual and past extropies are generally more stable. In this paper, we extend the concept of cumulative extropy which includes both cumulative inaccuracy and dynamic versions, such as cumulative residual inaccuracy and cumulative past inaccuracy. By using these measures, we characterize specific lifetime distributions and explore some generalized results. Additionally, we find that these inaccuracy measures can uniquely identify the underlying distributions, and we also characterize a few specific lifetime distributions. Two non-parametric estimators for this measure are provided and their performances are compared via some simulation studies. Finally, we illustrate our method in a real data set.

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Publication Details

Journal
Filomat
Published
2025-01-01
DOI
https://doi.org/10.2298/fil2508771h
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

Extropy: Dynamic cumulative past and residual inaccuracy measures with applications

Majid Hashempour‎, Abdolsaeed Toomaj, Mohammad Reza Kazemi
Filomat
Statistical Distribution Estimation and Applications
article

Extropy: Dynamic cumulative past and residual inaccuracy measures with applications

Majid Hashempour‎, Abdolsaeed Toomaj, Mohammad Reza Kazemi
article en

Abstract

In comparison to PDF-based measures which provided by extropy, the CDF-based measures of cumulative residual and past extropies are generally more stable. In this paper, we extend the concept of cumulative extropy which includes both cumulative inaccuracy and dynamic versions, such as cumulative residual inaccuracy and cumulative past inaccuracy. By using these measures, we characterize specific lifetime distributions and explore some generalized results. Additionally, we find that these inaccuracy measures can uniquely identify the underlying distributions, and we also characterize a few specific lifetime distributions. Two non-parametric estimators for this measure are provided and their performances are compared via some simulation studies. Finally, we illustrate our method in a real data set.

FilomatVol. 39(8)
University of Hormozgan (IR), Gonbad Kavous University (IR), Fasa University of Medical Sciences (IR), Fasa University
Openalex Percentile: Top 80%
Statistical Distribution Estimation and Applications
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