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The lifetimes of subjects which are left-censored lie below a threshold value or a limit of detection. A popular tool used to handle left-censored data is the reversed hazard rate. In this work, we study the properties and develop…

Statistics Theory · Mathematics 2022-12-27 G. Asha , Durga Vasudevan

This paper introduces a new generalization of the power generalized Weibull distribution called the generalized power generalized Weibull distribution. This distribution can also be considered as a generalization of Weibull distribution.…

Statistics Theory · Mathematics 2018-10-16 Mahmoud Ali Selim

It is standard practice for covariates to enter a parametric model through a single distributional parameter of interest, for example, the scale parameter in many standard survival models. Indeed, the well-known proportional hazards model…

Methodology · Statistics 2020-08-10 Kevin Burke , Gilbert MacKenzie

We consider a log-linear model for survival data, where both the location and scale parameters depend on covariates and the baseline hazard function is completely unspecified. This model provides the flexibility needed to capture many…

Methodology · Statistics 2019-01-16 Kevin Burke , Frank Eriksson , C. B. Pipper

In this article,a three parameter generalisation of inverse lindley distribution is obtained, with the purpose of obtaining a more flexible model relative to the behaviour of hazard rate functions. Various statistical properties such as…

Statistics Theory · Mathematics 2018-08-23 Rameesa Jan , T. R. Jan , Peer Bilal Ahmad

The estimation of marginal loan write-off probabilities is a non-trivial task when modelling the loss given default (LGD) risk parameter in credit risk. We explore two types of survival models in estimating the overall write-off probability…

Risk Management · Quantitative Finance 2026-03-13 Arno Botha , Mohammed Gabru , Marcel Muller , Janette Larney

The mean residual life function is a key functional for a survival distribution. It has a practically useful interpretation as the expected remaining lifetime given survival up to a particular time point, and it also characterizes the…

Methodology · Statistics 2018-10-11 Valerie Poynor , Athanasios Kottas

The density ratio model (DRM) is a semiparametric model that relates the distributions from multiple samples to a nonparametrically defined reference distribution via exponential tilting, with finite-dimensional parameters governing their…

Methodology · Statistics 2025-11-13 James Hugh McVittie , Archer Gong Zhang

We consider a parametric modelling approach for survival data where covariates are allowed to enter the model through multiple distributional parameters, i.e., scale and shape. This is in contrast with the standard convention of having a…

Methodology · Statistics 2021-11-17 Fatima-Zahra Jaouimaa , Il Do Ha , Kevin Burke

This paper introduces one new multivariate volatility model that can accommodate an appropriately defined network structure based on low-frequency and high-frequency data. The model reduces the number of unknown parameters and the…

Statistical Finance · Quantitative Finance 2022-04-28 Huiling Yuan , Guodong Li , Junhui Wang

We consider generalized linear regression analysis with left-censored covariate due to the lower limit of detection. Complete case analysis by eliminating observations with values below limit of detection yields valid estimates for…

Methodology · Statistics 2014-12-09 Shengchun Kong , Bin Nan

Survival models incorporating cure fractions, commonly known as cure fraction models or long-term survival models, are widely employed in epidemiological studies to account for both immune and susceptible patients in relation to the failure…

Methodology · Statistics 2023-11-14 Agatha Rodrigues , Patrick Borges

In survival or reliability studies, the mean residual life or life expectancy is an important characteristic of the model. Here, we study the limiting behaviour of the mean residual life, and derive an asymptotic expansion which can be used…

Statistics Theory · Mathematics 2007-06-13 David M. Bradley , Ramesh C. Gupta

Survival models are a popular tool for the analysis of time to event data with applications in medicine, engineering, economics, and many more. Advances like the Cox proportional hazard model have enabled researchers to better describe…

Machine Learning · Statistics 2021-02-16 Stefan Groha , Sebastian M Schmon , Alexander Gusev

The mean residual life function is a key functional for a survival distribution. It has a practically useful interpretation as the expected remaining lifetime given survival up to a particular time point, and it also characterizes the…

Applications · Statistics 2024-01-26 Valerie Poynor , Athanasios Kottas

A class of estimating functions is introduced for the regression parameter of the Cox proportional hazards model to allow unknown failure statuses on some study subjects. The consistency and asymptotic normality of the resulting estimators…

Statistics Theory · Mathematics 2007-08-22 Irene Gijbels , Danyu Lin , Zhiliang Ying

This paper describes a pattern recognition approach aiming to estimate fuel cell duration time from electrochemical impedance spectroscopy measurements. It consists in first extracting features from both real and imaginary parts of the…

Machine Learning · Statistics 2013-12-30 Raïssa Onanena , Faicel Chamroukhi , Latifa Oukhellou , Denis Candusso , Patrice Aknin , Daniel Hissel

In recent years research on credit risk modelling has mainly focused on default probabilities. Recovery rates are usually modelled independently, quite often they are even assumed constant. Then, however, the structural connection between…

Risk Management · Quantitative Finance 2015-03-06 Alexander F. R. Koivusalo , Rudi Schäfer

The Birnbaum-Saunders distribution, also known as the fatigue-life distribution, is frequently used in reliability studies. We obtain adjustments to the Birnbaum--Saunders profile likelihood function. The modified versions of the likelihood…

Methodology · Statistics 2008-04-06 Audrey H. M. A. Cysneiros , Francisco Cribari-Neto , Carlos A. G. Araujo

Prognostic models in survival analysis are aimed at understanding the relationship between patients' covariates and the distribution of survival time. Traditionally, semi-parametric models, such as the Cox model, have been assumed. These…

Machine Learning · Statistics 2020-11-06 Denise Rava , Jelena Bradic