A Bayesian latent spatial model for mapping the cortical signature of progression to Alzheimer's disease

DOI10.1002/cjs.11588OpenAlexW3133319420MaRDI QIDQ6059488

Hakmook Kang, Galin L. Jones, Ning Dai, Unnamed Author

Publication date: 2 November 2023

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

Full work available at URL: https://doi.org/10.1002/cjs.11588

zbMATH Keywords

spatial statisticssurvival analysisAlzheimer's diseaseBayesian modellinglongitudinal studies

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• BFLCRM: a Bayesian functional linear Cox regression model for predicting time to conversion to Alzheimer's disease
• Strong consistency of multivariate spectral variance estimators in Markov chain Monte Carlo
• Multivariate initial sequence estimators in Markov chain Monte Carlo
• A Unified Framework for Fitting Bayesian Semiparametric Models to Arbitrarily Censored Survival Data, Including Spatially Referenced Data
• Multivariate output analysis for Markov chain Monte Carlo
• Bayesian survival analysis

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