Spatial survival modelling of business re-opening after Katrina: Survival modelling compared to spatial probit modelling of re-opening within 3, 6 or 12 months

DOI10.1177/1471082X20967158OpenAlexW3111203682MaRDI QIDQ3389297

Virgilio Gómez-Rubio, Roger S. Bivand

Publication date: 10 May 2021

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x20967158

zbMATH Keywords

Markov chain Monte CarloBayesian inferenceintegrated nested Laplace approximationbusiness decisionsspatial probit modelsspatial survival models

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• survival
• R-Geo
• Arc_Mat
• INLA
• spBayes
• spBayesSurv
• spatsurv
• spatialprobit
• ProbitSpatial

Cites Work

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• Modeling survival data: extending the Cox model
• Penalising model component complexity: a principled, practical approach to constructing priors
• Bayesian Spatial Survival Models
• Applied Survival Analysis Using R
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• Nonparametric Estimation from Incomplete Observations
• Bayesian Measures of Model Complexity and Fit
• Applied Spatial Data Analysis with R
• A Unified Framework for Fitting Bayesian Semiparametric Models to Arbitrarily Censored Survival Data, Including Spatially Referenced Data
• Bayesian Inference with INLA
• Bayesian survival analysis

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