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Description

Bernstein Polynomial Based Semiparametric Survival Analysis.

A set of reliable routines to ease semiparametric survival regression modeling based on Bernstein polynomials. 'spsurv' includes proportional hazards, proportional odds and accelerated failure time frameworks for right-censored data. RV Panaro (2020) <arXiv:2003.10548>.

spsurv

An R package for semi-parametric survival analysis.

The spsurv package was designed to contribute with a flexible set of semi-parametric survival regression modelings, including proportional hazards (PH), proportional odds (PO), and accelerated failure time (AFT) models for right-censored data.

  • Install and load the spsurv package using the devtools package.
install.packages("devtools")

library(devtools)
install_github("rvpanaro/spsurv")
  • Check out the main fitter function examples.
library("KMsurv")
data("larynx")

library(spsurv)

## Maximum Likelihood
fit <- spbp(Surv(time, delta)~age+factor(stage),
                    approach = "mle",  data = larynx)
summary(fit)      

## NUTS sampling (Bayesian)
fit2 <- spbp(Surv(time, delta)~age+factor(stage),
                     approach = "bayes",  data = larynx,
                     iter = 2000, chains = 1, warmup = 1000)
summary(fit2)

The spsurv already provides:

  • Integration with Stan software.
  • Estimates either in Bayesian or Frequentist (point estimate) inferential approaches.
  • Three survival regression classes: PH, PO and AFT.
  • Six distinct prior specifications in a Bayesian analysis.
Metadata

Version

1.0.0

License

Unknown

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