In this paper, we examine mixture models to model heterogeneous survival data. Mixture of Gamma distributions, mixture of Lognormal distributions and mixture of Weibull distributions were tested for the best fit to the real survival datasets. Various properties of the proposed mixture models were discussed. Maximum likelihood estimations of the parameters of mixture models were obtained by the EM algorithm. The mixture models were successfully applied for modeling two real heterogeneous survival datasets. © 2012 Pakistan Journal of Statistics
Survival models are being widely applied to the engineering field to model time-to-event data once c...
Finite mixtures of distributions have provided a mathematical-based approach to the statistical mode...
A general method for deriving new survival distributions from old is presented. This yields a class...
In this paper we propose a mixture of two different distributions such as Exponential-Gamma, Exponen...
In this paper we propose a mixture of two different distributions such as Exponential-Gamma, Exponen...
In this study survival mixture model of three components was proposed for the analysis of heterogene...
A parametric mixture model of three different distributions is proposed to analyse heterogeneous sur...
Aims: In this study a survival mixture model of three components is considered to analyse survival d...
Previous studies showed that two components of survival mixture model performed better than pure cla...
WOS: 000284410300004In this article, we propose a mixture of extended exponential-geometric distribu...
Mixture modeling is commonly used to model categorical latent variables that represent subpopulation...
In this article we use Bayesian methods to fit a Weibull mixture model with an unknown number of com...
Frailty mixture survival models are statistical models which allow for a cured fraction and frailty....
Heterogeneity exists on a data set when samples from different classes are merged into the data set....
Survival analysis is a widely used method to establish a connection between a time to event outcome ...
Survival models are being widely applied to the engineering field to model time-to-event data once c...
Finite mixtures of distributions have provided a mathematical-based approach to the statistical mode...
A general method for deriving new survival distributions from old is presented. This yields a class...
In this paper we propose a mixture of two different distributions such as Exponential-Gamma, Exponen...
In this paper we propose a mixture of two different distributions such as Exponential-Gamma, Exponen...
In this study survival mixture model of three components was proposed for the analysis of heterogene...
A parametric mixture model of three different distributions is proposed to analyse heterogeneous sur...
Aims: In this study a survival mixture model of three components is considered to analyse survival d...
Previous studies showed that two components of survival mixture model performed better than pure cla...
WOS: 000284410300004In this article, we propose a mixture of extended exponential-geometric distribu...
Mixture modeling is commonly used to model categorical latent variables that represent subpopulation...
In this article we use Bayesian methods to fit a Weibull mixture model with an unknown number of com...
Frailty mixture survival models are statistical models which allow for a cured fraction and frailty....
Heterogeneity exists on a data set when samples from different classes are merged into the data set....
Survival analysis is a widely used method to establish a connection between a time to event outcome ...
Survival models are being widely applied to the engineering field to model time-to-event data once c...
Finite mixtures of distributions have provided a mathematical-based approach to the statistical mode...
A general method for deriving new survival distributions from old is presented. This yields a class...