Kernel-based Estimation of Ageing Intensity Function: Properties and Applications

Authors

  • R S Rasin Cochin Unvierstiy of Science and Technology, Kochi, Kerala, India
  • S M Sunoj Cochin Unvicersity of Sceience and Technology, Kochi, Kerala, India
  • Rakesh Poduval MMO Information Technology PVT. LTD. 6/405-1, Cochin 682021, Kerala, India

DOI:

https://doi.org/10.17713/ajs.v52i5.1497

Abstract

The notion of ageing plays an important role in reliability and survival analysis as it is an inherent property of all systems and products. Jiang, Ji, and Xiao (2003) proposed a new quantitative measure, known as ageing intensity (AI) function, an alternative measure
to study the ageing pattern of probability models. In this paper, we propose a nonparametric estimator for ageing intensity function. Asymptotic properties of the estimator are established under suitable regularity conditions. A set of simulation studies are carried
out based on various probability models to examine the performance of estimator and to establish its efficiency over the classical estimator. The usefulness of the estimator is also examined through a real data set.

Author Biographies

R S Rasin, Cochin Unvierstiy of Science and Technology, Kochi, Kerala, India

Assistant Professor, Department of Statistics

S M Sunoj, Cochin Unvicersity of Sceience and Technology, Kochi, Kerala, India

Professor, Department of Statistics

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Published

2023-09-11

How to Cite

Rasin, R. S., S M Sunoj, & Rakesh Poduval. (2023). Kernel-based Estimation of Ageing Intensity Function: Properties and Applications. Austrian Journal of Statistics, 52(5), 16–33. https://doi.org/10.17713/ajs.v52i5.1497