Survival analysis for the inverse Gaussian distribution with the Gibbs sampler

DOI10.1080/02664763.2020.1828314OpenAlexW3091488608MaRDI QIDQ5085639

Raj S. Chhikara, Kalanka P. Jayalath

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1828314

zbMATH Keywords

Gibbs samplercensoringBayesian inferencebootstrap testkernel density estimatefiducial inference

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• R
• CODA
• BayesDA
• fitdistrplus
• arm
• gsubfn

Cites Work

• The art of progressive censoring. Applications to reliability and quality
• Bayesian analysis of an inverse Gaussian correlated frailty model
• The inverse Gaussian distribution. Statistical theory and applications
• Inference from iterative simulation using multiple sequences
• On fiducial generators
• Statistical Properties of Inverse Gaussian Distributions. I
• Sampling-Based Approaches to Calculating Marginal Densities
• Bayesian and fiducial inference for the inverse gaussian distribution via Gibbs sampler
• The Inverse Gaussian Distribution as a Lifetime Model
• Gibbs Sampling Methods for Stick-Breaking Priors
• Bayesian and likelihood inference for cure rates based on defective inverse Gaussian regression models
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