Results 1 to 10 of about 80 (78)

A generalized Gompertz promotion time cure model and its fitness to cancer data [PDF]

Heliyon
The cure models based on standard distributions like exponential, Weibull, lognormal, Gompertz, gamma, are often used to analyze survival data from cancer clinical trials with long-term survivors.
Ayesha Tahira, Muhammad Yameen Danish
doaj   +2 more sources

Epidemiological modeling of COVID-19 data with Advanced statistical inference based on Type-II progressive censoring [PDF]

Heliyon
This research proposes the Kavya-Manoharan Unit Exponentiated Half Logistic (KM-UEHL) distribution as a novel tool for epidemiological modeling of COVID-19 data.
Naif Alotaibi, A.S. Al-Moisheer, Amal S. Hassan, Ibrahim Elbatal, Salem A. Alyami, Ehab M. Almetwally   +5 more
doaj   +2 more sources

Asymptotic normality of the relative error regression function estimator for censored and time series data

Dependence Modeling, 2021
Consider a survival time study, where a sequence of possibly censored failure times is observed with d-dimensional covariate The main goal of this article is to establish the asymptotic normality of the kernel estimator of the relative error regression ...
Bouhadjera Feriel, Saïd Elias Ould
doaj   +1 more source

Inferences for Joint Modelling of Repeated Ordinal Scores and Time to Event Data

Computational and Mathematical Methods in Medicine, Volume 11, Issue 3, Page 281-295, 2010., 2010
In clinical trials and other follow‐up studies, it is natural that a response variable is repeatedly measured during follow‐up and the occurrence of some key event is also monitored. There has been a considerable study on the joint modelling these measures together with information on covariates.
Arindom Chakraborty, Kalyan Das
wiley   +1 more source

The Poisson-exponential regression model under different latent activation schemes [PDF]

, 2012
In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution ...
Cancho, Vicente Garibay, Louzada,Francisco, Cancho,Vicente G, Cancho, Vicente G, Barriga, Gladys Dorotea Cacsire [UNESP], Barriga, Gladys Dorotea Cacsire, Barriga,Gladys D.C, Louzada, Francisco   +7 more
core   +1 more source

Nonparametric density estimation in presence of bias and censoring

, 2009
Adaptive estimation, Minimax rate, Biased data, Right-censoring, Nonparametric penalized contrast estimator, 62G07, 62N01,
Comte, Fabienne, A. Guilloux, Brunel, Elodie, Guilloux, Agathe, F. Comte, E. Brunel   +5 more
core   +1 more source

Reliability inference of a multicomponent stress-strength model for exponentiated Pareto distribution based on progressive first failure censored samples

Journal of Radiation Research and Applied Sciences
Multicomponent stress-strength (MC-SS) analysis is crucial for risk management and decision-making in various fields such as engineering, manufacturing, and quality control.
Najwan Alsadat, Amal S. Hassan, Mohammed Elgarhy, Mustapha Muhammad, Ehab M. Almetwally   +4 more
doaj   +1 more source

Objective Bayesian reference analysis for the Poisson process model in presence of recurrent events data

, 2010
Reference analysis, Recurrent events, Intensity function, Poisson process, Bayesian inference, 63F15, 62N01,
José Bernardo, José Miguel Bernardo, Vera Lucia Tomazella, Vera Tomazella   +3 more
core   +1 more source

Progressive censoring methodology: an appraisal

, 2007
Progressive censoring, Order statistics, Life-testing experiment, Bounds, Generalized order statistics, Characterizations, Markov property, Likelihood inference, Reliability sampling plans, Goodness-of-fit tests, Prediction, Competing risks, Step-stress ...
N. Balakrishnan
core   +1 more source

Mixed Inverse Gaussian Analysis of Covariance for Censored Data: A Bayesian Approach

Journal of Mathematics, Volume 2025, Issue 1, 2025.
This paper proposes a model for analysis of covariance (ANCOVA) of censored data obtained from a positively skewed population by using the mixed inverse Gaussian (MIG) distribution. A hierarchical fully Bayesian approach is employed to fit and infer about the proposed model.
Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh, Gholamhossein Yari, Barbara Martinucci   +4 more
wiley   +1 more source