The zero-inflated promotion cure rate model applied to financial data on time-to-default

Oliveira, Mauro R.; Moreira, Fernando; Louzada, Francisco

doi:10.1080/23322039.2017.1395950

Cited by 7 publications

(8 citation statements)

References 16 publications

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“…Different distributions can also be considered for the competitive causes associated with the occurrence of the event of interest. Moreover, our model generalizes other recent proposed models as the unified cure-rate models [8], and the mixture and promotion ZICR models [4,6]. The popular mixture cure model [1] and the promotion cure model [3] are also particular cases of the model proposed in this paper.…”

Section: Final Remarksmentioning

confidence: 57%

“…The unified ZICR model (1) generalizes a variety of survival models with and without zero-inflation. The two ZICR models already proposed by [6] and [4] are examples of its particular cases. If a = a m = p and b = b m = c × p we have that…”

Section: Methodsmentioning

confidence: 99%

“…Although it is usual the survival models assume that the variable time should be greater than zero, there is a diversity of phenomena in which we can find a considerable proportion of individuals with times equal to zero, which affects the survival curve by deflating its initial value to values smaller than 1. Statistically speaking, such peculiarity is the so called zero-inflation [2,4,6].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is important that survival models include the two features described above: zero-inflation and cure-rate. To the best of our knowledge, there are just two proposed models for continuous lifetime datasets with values equal to zero and cure rate [4,6]. The first one is the standard mixture ZICR model [6], which generalizes the mixture cure-rate model [1].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the unified zero-inflated cure-rate survival models

Louzada¹,

Ramos²,

Souza³

et al. 2019

Preprint

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Section: Final Remarksmentioning

confidence: 57%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the unified zero-inflated cure-rate survival models

Louzada¹,

Ramos²,

Souza³

et al. 2019

Preprint

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“…Pal & Balakrishnan, 2018). Cure rate models have been applied extensively on cancer survival data for cancers with relatively better prognosis (e.g., melanoma, breast cancer, leukemia and prostate cancer), recidivism studies, and defaulting on a loan in credit risk assessment studies (Maller & Zhou, 1996;de Oliveira et al, 2017;Ibrahim et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Version of the EM Algorithm for Mixture Cure Rate Model with Exponentiated Weibull Family of Lifetimes

Barui,

Pal,

Mishra

et al. 2021

Preprint

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Handling missing values plays an important role in the analysis of survival data, especially, the ones marked by cure fraction. In this paper, we discuss the properties and implementation of stochastic approximations to the expectation-maximization (EM) algorithm to obtain maximum likelihood (ML) type estimates in situations where missing data arise naturally due to right censoring and a proportion of individuals are immune to the event of interest. A flexible family of three parameter exponentiated-Weibull (EW) distributions is assumed to characterize lifetimes of the non-immune individuals as it accommodates both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub) hazard functions. To evaluate the performance of the SEM algorithm, an extensive simulation study is carried out under various parameter settings. Using likelihood ratio test we also carry out model discrimination within the EW family of distributions. Furthermore, we study the robustness of the SEM algorithm with respect to outliers and algorithm starting values. Few scenarios where stochastic EM (SEM) algorithm outperforms the well-studied EM algorithm are also examined in the given context. For further demonstration, a real survival data on cutaneous melanoma is analyzed using the proposed cure rate model with EW lifetime distribution and the proposed estimation technique. Through this data, we illustrate the applicability of the likelihood ratio test towards rejecting several well-known lifetime distributions that are nested within the wider class of EW distributions.

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Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality

Hwang

Chu

2020

J Financ Serv Res

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The zero-inflated promotion cure rate model applied to financial data on time-to-default

Cited by 7 publications

References 16 publications

On the unified zero-inflated cure-rate survival models

On the unified zero-inflated cure-rate survival models

A Stochastic Version of the EM Algorithm for Mixture Cure Rate Model with Exponentiated Weibull Family of Lifetimes

Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality

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