Inverse Lindley power series distributions : a new compounding family and regression model with censored data

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Détails bibliographiques
Publié dans:Journal of applied statistics. - 1991. - 49(2022), 13 vom: 13., Seite 3451-3476
Auteur principal: Shakhatreh, Mohammed K (Auteur)
Autres auteurs: Dey, Sanku, Kumar, Devendra
Format: Article en ligne
Langue:English
Publié: 2022
Accès à la collection:Journal of applied statistics
Sujets:Journal Article Lindley distribution Monte Carlo simulation inverse Lindley power series distributions maximum-likelihood estimators regression model
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520 |a 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 
650 4 |a Journal Article 
650 4 |a Lindley distribution 
650 4 |a Monte Carlo simulation 
650 4 |a inverse Lindley power series distributions 
650 4 |a maximum-likelihood estimators 
650 4 |a regression model 
700 1 |a Dey, Sanku  |e verfasserin  |4 aut 
700 1 |a Kumar, Devendra  |e verfasserin  |4 aut 
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