Package: survstan 0.1.0

survstan: Fitting Survival Regression Models via 'Stan'

Parametric survival regression models under the maximum likelihood approach via 'Stan'. Implemented regression models include accelerated failure time (AFT) models, proportional hazards (PH) models, proportional odds (PO) models, accelerated hazard (AH) models, Yang and Prentice (YP) models, and extended hazard (EH) models. Available baseline survival distributions include exponential, Weibull, log-normal, log-logistic, gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. The baseline survival distribution can be further modeled using Bernstein polynomails' approximation of the baseline hazard function. References: Lawless (2002) <ISBN:9780471372158>; Bennett (1982) <doi:10.1002/sim.4780020223>; Chen and Wang(2000) <doi:10.1080/01621459.2000.10474236>; Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>.

Authors:Fabio Demarqui [aut, cre, cph], Andrew Johnson [ctb]

survstan_0.1.0.tar.gz
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survstan.pdf |survstan.html✨
survstan/json (API)
NEWS

# Install 'survstan' in R:
install.packages('survstan', repos = c('https://fndemarqui.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fndemarqui/survstan/issues

Pkgdown site:https://fndemarqui.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • gastric - Gastric cancer data set
  • ipass - IRESSA Pan-Asia Study (IPASS) data set

On CRAN:

cpp

4.50 score 2 stars 63 scripts 260 downloads 33 exports 77 dependencies

Last updated 6 months agofrom:c1572ed0a9. Checks:1 ERROR, 10 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILJan 27 2025
R-4.5-win-x86_64WARNINGJan 27 2025
R-4.5-mac-x86_64WARNINGJan 27 2025
R-4.5-mac-aarch64WARNINGJan 27 2025
R-4.5-linux-x86_64WARNINGJan 27 2025
R-4.4-win-x86_64WARNINGJan 27 2025
R-4.4-mac-x86_64WARNINGJan 27 2025
R-4.4-mac-aarch64WARNINGJan 27 2025
R-4.3-win-x86_64WARNINGJan 27 2025
R-4.3-mac-x86_64WARNINGJan 27 2025
R-4.3-mac-aarch64WARNINGJan 27 2025

Exports:aftregahregbernsteincross_timedggprenticedggstacydgompertzdpexpehregestimatesggresidualshpexpHpexppggprenticepggstacypgompertzphregpiecewiseporegppexpqggprenticeqggstacyqgompertzqpexprank_modelsrggprenticerggstacyrgompertzrpexpsetidytime_gridypreg

Dependencies:abindactuarbackportsBHbroomcallrcheckmateclicodetoolscolorspacecpp11descdigestdistributionaldoFuturedplyrexpintextraDistrfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegridExtragtableinlineisobanditeratorslabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivparallellypillarpkgbuildpkgconfigposteriorprocessxpspurrrQuickJSRR6rbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackrlangrstanrstantoolsscalesStanHeadersstringistringrsurvivaltensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
The 'survstan' package.survstan-package survstan
Fitting Accelerated Failure Time Modelsaftreg
Fitting Accelerated Hazard Modelsahreg
Akaike information criterionAIC.survstan
anova method for survstan modelsanova.survstan
Bernstein polynomialbernstein
Estimated regression coefficientscoef.survstan
Confidence intervals for the regression coefficientsconfint.survstan
Generic S3 method cross_timecross_time
Computes the crossing survival timescross_time.survstan
Fitting Extended Hazard Modelsehreg
Support Functions for 'emmeans'emmeans-survstan-helpers recover_data.ehreg recover_data.survstan recover_data.ypreg
Parameters estimates of a survstan modelestimates
Extract AIC from a Fitted ModelextractAIC.survstan
Gastric cancer data setgastric
The Generalized Gamma Distribution (Prentice's alternative parametrization)dggprentice ggprentice pggprentice qggprentice rggprentice
Generic S3 method ggresidualsggresiduals
ggresiduals method for survstan modelsggresiduals.survstan
The Generalized Gamma Distribution (Stacy's original parametrization)dggstacy ggstacy pggstacy qggstacy rggstacy
The Gompertz Distributiondgompertz Gompertz gompertz Hgompertz hgompertz pgompertz qgompertz rgompertz
IRESSA Pan-Asia Study (IPASS) data setipass
Extract Log-Likelihood from a Fitted ModellogLik.survstan
Model.matrix method for survstan modelsmodel.matrix.survstan
Hazard and cumulative hazard functions of the PE distributionHpexp hpexp pehaz
Probability function, distribution function, quantile function and random generation for the Piecewise Exponential (PE) distribution.dpexp pexp ppexp qpexp rpexp
Fitting Proportional Hazards Modelsphreg
Piecewise baselinepiecewise
Fitting Proportional Odds Modelsporeg
Print the summary.survstan outputprint.summary.survstan
Rank a collection of survstan modelsrank_models
residuals method for survstan modelsresiduals.survstan
Generic S3 method sese
Estimated standard errorsse.survstan
Summary for a survstan objectsummary.survstan
survfit method for survstan modelssurvfit.survstan
Tidy a survstan objecttidy.survstan
Time gridtime_grid
Variance-covariance matrixvcov.survstan
Fitting Yang and Prentice Modelsypreg