On Some Reliability Aspects of Inverse Kies Distribution and Applications in Cancer Research
- 1Department of Statistics, University of Kerala, Trivandrum, 695581, India
Abstract
The inverse Kies distribution (IKD) of Kumar and Dharmaja [Inverse Kies distribution: properties and applications, South African Statistical Journal, 2017] is a useful distribution for modelling the complete lifetime of systems with bathtub-shaped or reverse S-shaped hazard rate functions where both the Weibull and the inverse Weibull models are not suitable. In this paper, we discuss some important statistical properties of the distribution with special emphasis on its characteristics related to reliability studies and order statistics along with the derivation of some important properties of the distribution such as expressions for characteristic function, incomplete moments, L moments etc. We discuss the parameter estimation by considering the Bayesian estimation of the two unknown shape parameters of the IKD. Also, the performance of the estimators under the squared error loss function (SELF) and general entropy loss function (GELF) loss functions are compared through Monte Carlo simulation study and the usefulness of the proposed model is illustrated with the help of real-life cancer survival datasets. The results demonstrate that the IKD provides a robust and accurate model for complex survival data, highlighting its potential utility in medical reliability analysis and prognostic modeling.
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BibTeX
@article{kumar2026some,
title = {{On Some Reliability Aspects of Inverse Kies Distribution and Applications in Cancer Research}},
author = {C. Satheesh Kumar and Pallavi Krishna S},
journal = {Reliability: Theory \& Applications},
year = {2026},
month = jun,
doi = {10.66721/bzmp4p67},
url = {https://doi.org/10.66721/bzmp4p67},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - On Some Reliability Aspects of Inverse Kies Distribution and Applications in Cancer Research
AU - C. Satheesh Kumar
AU - Pallavi Krishna S
PY - 2026
DA - 2026/06/01
JO - Reliability: Theory & Applications
DO - 10.66721/bzmp4p67
UR - https://doi.org/10.66721/bzmp4p67
AB - The inverse Kies distribution (IKD) of Kumar and Dharmaja [Inverse Kies distribution: properties and applications, South African Statistical Journal, 2017] is a useful distribution for modelling the complete lifetime of systems with bathtub-shaped or reverse S-shaped hazard rate functions where both the Weibull and the inverse Weibull models are not suitable. In this paper, we discuss some important statistical properties of the distribution with special emphasis on its characteristics related to reliability studies and order statistics along with the derivation of some important properties of the distribution such as expressions for characteristic function, incomplete moments, L moments etc. We discuss the parameter estimation by considering the Bayesian estimation of the two unknown shape parameters of the IKD. Also, the performance of the estimators under the squared error loss function (SELF) and general entropy loss function (GELF) loss functions are compared through Monte Carlo simulation study and the usefulness of the proposed model is illustrated with the help of real-life cancer survival datasets. The results demonstrate that the IKD provides a robust and accurate model for complex survival data, highlighting its potential utility in medical reliability analysis and prognostic modeling.
SN - 1932-2321
ER -