Package: spBayesSurv 1.1.8
spBayesSurv: Bayesian Modeling and Analysis of Spatially Correlated Survival Data
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>.
Authors:
spBayesSurv_1.1.8.tar.gz
spBayesSurv_1.1.8.tar.gz(r-4.5-noble)spBayesSurv_1.1.8.tar.gz(r-4.4-noble)
spBayesSurv_1.1.8.tgz(r-4.4-emscripten)spBayesSurv_1.1.8.tgz(r-4.3-emscripten)
spBayesSurv.pdf |spBayesSurv.html✨
spBayesSurv/json (API)
# Install 'spBayesSurv' in R: |
install.packages('spBayesSurv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- LeukSurv - The Leukemia Survival Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:7510450162. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 27 2024 |
Exports:anovaDDPbaselineBF.SpatDensRegbsplinecox.snell.survregbayesfrailtyGAFTfrailtypriorGetCurvesindeptCoxphmakepredictcall.bsplineplot.anovaDDPplot.frailtyGAFTplot.indeptCoxphplot.SpatDensRegplot.spCopulaCoxphplot.spCopulaDDPplot.SuperSurvRegBayesplot.survregbayesplot.survregbayes2predict.bsplineprint.frailtyGAFTprint.indeptCoxphprint.SpatDensRegprint.spCopulaCoxphprint.summary.frailtyGAFTprint.summary.indeptCoxphprint.summary.SpatDensRegprint.summary.spCopulaCoxphprint.summary.SuperSurvRegBayesprint.summary.survregbayesprint.summary.survregbayes2print.SuperSurvRegBayesprint.survregbayesprint.survregbayes2SpatDensRegspCopulaCoxphspCopulaDDPsummary.frailtyGAFTsummary.indeptCoxphsummary.SpatDensRegsummary.spCopulaCoxphsummary.SuperSurvRegBayessummary.survregbayessummary.survregbayes2SuperSurvRegBayessurvregbayessurvregbayes2
Dependencies:codadotCall64fieldslatticemapsMASSMatrixRcppRcppArmadillospamsurvivalviridisLite
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Bayesian Nonparametric Survival Model | anovaDDP |
Stratification effects on baseline functions | baseline |
Generate a Cubic B-Spline Basis Matrix | bspline makepredictcall.bspline |
Cox-Snell Diagnostic Plot | cox.snell.survregbayes |
Generalized Accelerated Failure Time Frailty Model | frailtyGAFT print.frailtyGAFT print.summary.frailtyGAFT summary.frailtyGAFT |
Frailty prior specification | frailtyprior |
Density, Survival, and Hazard Estimates | GetCurves plot.anovaDDP plot.frailtyGAFT plot.indeptCoxph plot.SpatDensReg plot.spCopulaCoxph plot.spCopulaDDP plot.SuperSurvRegBayes plot.survregbayes |
Bayesian Proportional Hazards Model | indeptCoxph print.indeptCoxph print.summary.indeptCoxph summary.indeptCoxph |
The Leukemia Survival Data | LeukSurv |
Evaluate a Cubic Spline Basis | predict.bspline |
Bayesian Nonparametric Spatially Smoothed Density Estimation | BF.SpatDensReg print.SpatDensReg print.summary.SpatDensReg SpatDensReg summary.SpatDensReg |
Marginal Bayesian Proportional Hazards Model via Spatial Copula | print.spCopulaCoxph print.summary.spCopulaCoxph spCopulaCoxph summary.spCopulaCoxph |
Marginal Bayesian Nonparametric Survival Model via Spatial Copula | spCopulaDDP |
Bayesian Semiparametric Super Survival Model | print.summary.SuperSurvRegBayes print.SuperSurvRegBayes summary.SuperSurvRegBayes SuperSurvRegBayes |
Bayesian Semiparametric Survival Models | print.summary.survregbayes print.survregbayes summary.survregbayes survregbayes |
Bayesian Semiparametric Survival Models | plot.survregbayes2 print.summary.survregbayes2 print.survregbayes2 summary.survregbayes2 survregbayes2 |