Bayesian Modeling and Analysis of Spatially Correlated Survival Data
Bayesian Nonparametric Survival Model
Stratification effects on baseline functions
Generate a Cubic B-Spline Basis Matrix
Cox-Snell Diagnostic Plot
Generalized Accelerated Failure Time Frailty Model
Frailty prior specification
Density, Survival, and Hazard Estimates
Bayesian Proportional Hazards Model
Evaluate a Cubic Spline Basis
Bayesian Nonparametric Spatially Smoothed Density Estimation
Marginal Bayesian Proportional Hazards Model via Spatial Copula
Marginal Bayesian Nonparametric Survival Model via Spatial Copula
Bayesian Semiparametric Super Survival Model
Bayesian Semiparametric Survival Models
Bayesian Semiparametric Survival Models
Provides several Bayesian survival models for spatial/non-spatial survival data: proportional hazards (PH), accelerated failure time (AFT), proportional odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), generalized accelerated failure time (GAFT), and spatially smoothed Polya tree density estimation. The spatial dependence is modeled via frailties under PH, AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou, Hanson and Zhang (2020) <doi:10.18637/jss.v092.i09>.