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Related papers: A Fractional Survival Model

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In this paper, a family of neural network-based survival models is presented. The models are specified based on piecewise definitions of the hazard function and the density function on a partitioning of the time; both constant and linear…

Machine Learning · Statistics 2024-03-28 Olov Holmer , Erik Frisk , Mattias Krysander

A new lifetime model, named the Modi linear failure rate distribution, is suggested. This flexible model is capable of accommodating a wide range of hazard rate shapes, including decreasing, increasing, bathtub, upside-down bathtub, and…

Methodology · Statistics 2026-02-26 Lazhar Benkhelifa

This paper proposes a new extension of the linear failure rate (LFR) model to better capture real-world lifetime data. The model incorporates an additional shape parameter to increase flexibility. It helps model the minimum survival time…

Methodology · Statistics 2026-01-13 Suchismita Das , Akul Ameya , Cahyani Karunia Putri

Survival models capture the relationship between an accumulating hazard and the occurrence of a singular event stimulated by that accumulation. When the model for the hazard is sufficiently flexible survival models can accommodate a wide…

Methodology · Statistics 2024-03-04 Michael Betancourt

We introduce a general, flexible, parametric survival modelling framework which encompasses key shapes of hazard function (constant, increasing, decreasing, up-then-down, down-then-up), various common survival distributions (log-logistic,…

Methodology · Statistics 2019-01-11 Kevin Burke , M. C. Jones , Angela Noufaily

We address the problem of survival regression modelling with multivariate responses and nonlinear covariate effects. Our model extends the proportional hazards model by introducing several weakly-parametric elements: the marginal baseline…

Methodology · Statistics 2025-10-16 Na Lei , Mark A. Wolters , Wenqing He

Although proportional hazard rate model is a very popular model to analyze failure time data, sometimes it becomes important to study the additive hazard rate model. Again, sometimes the concept of the hazard rate function is abstract, in…

Statistics Theory · Mathematics 2017-05-30 Suchismita Das , Asok K. Nanda

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 conditional survival function of a time-to-event outcome subject to censoring and truncation is a common target of estimation in survival analysis. This parameter may be of scientific interest and also often appears as a nuisance in…

Methodology · Statistics 2024-08-20 Charles J. Wolock , Peter B. Gilbert , Noah Simon , Marco Carone

In this paper, we propose a fractional differential equation of order one-half, to model the evolution through time of the dynamics of accumulation and elimination of the contaminant in human organism with a deficient immune system, during…

Methodology · Statistics 2022-07-28 Komla Elom Adedje , Diakarya Barro

In this paper, we introduce a new extension of the generalized linear failure rate distributions. It includes some well-known lifetime distributions such as extension of generalized exponential and generalized linear failure rate…

Statistics Theory · Mathematics 2016-03-10 Mohammad Reza Kazemi , Ali Akbar Jafari , Saeid Tahmasebi

There are some real life issues that are exists in nature which has early failure. This type of problems can be modelled either by a complex distribution having more than one parameter or by finite mixture of some distribution. In this…

Statistics Theory · Mathematics 2024-08-30 Brijesh P. Singh , Utpal Dhar Das , Sandeep Singh

In this paper, we propose a flexible cure rate model with frailty term in latent risk, which is obtained by incorporating a frailty term in risk function of latent competing causes. The number of competing causes of the event of interest…

Medical investigations focusing on patient survival often generate not only a failure time for each patient but also a sequence of measurements on patient health at annual or semi-annual check-ups while the patient remains alive. Such a…

Methodology · Statistics 2016-01-18 Peter McCullagh , Walter Dempsey

A modification of the Drude dispersive model based on fractional time derivative is presented. The dielectric susceptibility is calculated analytically and simulated numerically, showing a good agreement between theoretical description and…

Computational Physics · Physics 2021-03-23 Karol Karpiński , Sylwia Zielińska - Raczyńska , David Ziemkiewicz

Trends in human longevity are puzzling, especially when considering the limits of human longevity. Partially, the conflicting assertions are based upon demographic evidence and the interpretation of survival and mortality curves using the…

Populations and Evolution · Quantitative Biology 2007-05-23 Byung Mook Weon

Survival models are used to analyze time-to-event data in a variety of disciplines. Proportional hazard models provide interpretable parameter estimates, but proportional hazards assumptions are not always appropriate. Non-parametric models…

Methodology · Statistics 2022-07-08 Richard D. Payne , Nilabja Guha , Bani K. Mallick

Survival analysis, or time-to-event modelling, is a classical statistical problem that has garnered a lot of interest for its practical use in epidemiology, demographics or actuarial sciences. Recent advances on the subject from the point…

Machine Learning · Computer Science 2021-07-28 Guillaume Ausset , Tom Ciffreo , Francois Portier , Stephan Clémençon , Timothée Papin

We calculate the survival probability of an immobile target surrounded by a sea of uncorrelated diffusive or subdiffusive evanescent traps, i.e., traps that disappear in the course of their motion. Our calculation is based on a fractional…

Statistical Mechanics · Physics 2015-06-11 E. Abad , S. B. Yuste , Katja Lindenberg

Assuming some regression model, it is common to study the conditional distribution of survival given covariates. Here, we consider the impact of further conditioning, specifically conditioning on a marginal survival function, known or…

Applications · Statistics 2016-10-11 Roxane Duroux , Cécile Chauvel , John O'Quigley
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