# Generalized inverse-Gaussian frailty models with application to TARGET neuroblastoma data

@article{Piancastelli2020GeneralizedIF, title={Generalized inverse-Gaussian frailty models with application to TARGET neuroblastoma data}, author={Luiza Sette C{\^a}mara Piancastelli and Wagner Barreto‐Souza and Vin{\'i}cius Diniz Mayrink}, journal={Annals of the Institute of Statistical Mathematics}, year={2020} }

A new class of survival frailty models based on the Generalized Inverse-Gaussian (GIG) distributions is proposed. We show that the GIG frailty models are flexible and mathematically convenient like the popular gamma frailty model. Furthermore, our proposed class is robust and does not present some computational issues experienced by the gamma model. By assuming a piecewise-exponential baseline hazard function, which gives a semiparametric flavour for our frailty class, we propose an EM…

## 4 Citations

### Reliability evaluation of repairable systems considering component heterogeneity using frailty model

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The failure processes of heterogeneous repairable systems with minimal repair assumption can be modelled by nonhomogeneous Poisson processes. One approach to describe an unobserved heterogeneity…

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The primary goal of this paper is to introduce a novel frailty model based on the weighted Lindley (WL) distribution for modeling clustered survival data. We study the statistical properties of the…

### The Pareto type I joint frailty-copula model for clustered bivariate survival data

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### Multivariate failure time distributions derived from shared frailty and copulas

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This paper revisits a broad family of multivariate failure time models proposed by Marshall and Olkin (JASA 83:834–841, 1988), and proposes a shared frailty model that accommodates both frailty and copulas, unlike the models that accommodate only one of them.

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