A Spatially Correlated Competing Risks Time-to-Event Model for Supercomputer GPU Failure Data

J Min, Y Hong, WQ Meeker, G Ostrouchov - arXiv preprint arXiv …, 2023 - arxiv.org
Graphics processing units (GPUs) are widely used in many high-performance computing
(HPC) applications such as imaging/video processing and training deep-learning models in …

Modeling geostatistical incomplete spatially correlated survival data with applications to COVID-19 mortality in Ghana

PA Allotey, O Harel - Spatial Statistics, 2023 - Elsevier
Survival models which incorporate frailties are common in time-to-event data collected over
distinct spatial regions. While incomplete data are unavoidable and a common complication …

Bayesian transformation model for spatial partly interval-censored data

M Qiu, T Hu - Journal of Applied Statistics, 2023 - Taylor & Francis
The transformation model with partly interval-censored data offers a highly flexible modeling
framework that can simultaneously support multiple common survival models and a wide …

[HTML][HTML] Mixed-Effects Parametric Proportional Hazard Model with Generalized Log-Logistic Baseline Distribution

MW Peter, SM Mwalili, AK Wanjoya… - Journal of Data Analysis …, 2023 - scirp.org
Clustered survival data are widely observed in a variety of setting. Most survival models
incorporate clustering and grouping of data accounting for between-cluster variability that …

Copula Functions for Spatial Survival Data Analysis

M Mohammadzadeh, N Ebrahimi… - Journal of Sciences …, 2023 - jsciences.ut.ac.ir
Many survival data analyses aim to assess the effect of different risk factors on survival time‎.‎
In some studies‎,‎ the survival times are correlated‎,‎ and the dependence between survival …