Inverse lindley power series distributions: anew compounding family and regressionmodel with censored data
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Applied Statistics
Abstract
This paper introduces a new class of distributions by compounding
the inverse Lindley distribution and power series distributions
which is called compound inverse Lindley power series (CILPS) distributions.
An important feature of this distribution is that the lifetime
of the component associated with a particular risk is not observable,
rather only the minimum lifetime value among all risks is observable.
Further, these distributions exhibit an unimodal failure rate. Various
properties of the distribution are derived. Besides, two special models
of the new family are investigated. The model parameters of the
two sub-models of the new family are obtained by the methods of
maximum likelihood, least square, weighted least square and maximum
product of spacing and compared them using the Monte Carlo
simulation study. Besides, the log compound inverse Lindley regression
model for censored data is proposed. Three real data sets are
analyzed to illustrate the flexibility and importance of the proposed
models.
Description
Keywords
Lindley distribution; inverse Lindley power series distributions; regression model; maximum-likelihood estimators; Monte Carlo simulation