R Under development (unstable) (2024-01-10 r85799 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
> 
> library(testthat)
> library(survobj)
> 
> test_check("survobj")
Loading required package: survival
Valid parameters to define a Exponential distribution are: 
lambda: for the canonical parameter of the distribution, or
surv, t: for the surviving proportion (no events) at time t, or
fail, t: for the failure proportion (events) at time t 

Valid parameters to define a Gompertz distribution are: 
scale and shape: for the canonical parameters of the distribution, or
surv, t and shape: for the surviving proportion (no events) at time t and shape, or
fail, t and shape: for the failure proportion (events) at time t and shape, or 

Valid parameters to define a loglogistic distribution are: 
scale and shape: for the canonical parameters of the distribution, or
surv, t and shape: for the surviving proportion (no events) at time t and shape, or
fail, t and shape: for the failure proportion (events) at time t and shape, or
intercept and scale: for values from a survreg regression

Valid parameters to define a lognormal distribution are: 
scale and shape: for the canonical parameters of the distribution, or
surv, t and shape: for the surviving proportion (no events) at time t and shape, or
fail, t and shape: for the failure proportion (events) at time t and shape, or
intercept and scale: for values from a survreg regression

Valid parameters to define a Piecewise Exponential distribution are: 
breaks and hazards: for the exponential hazard until each break, or
surv, breaks and segments : for the surviving proportion (no events) at the last break, or
fail, breaks and segments: for the failure proportion (events) at the last finite break 

Valid parameters to define a Weibull distribution are: 
scale and shape: for the canonical parameters of the distribution, or
surv, t and shape: for the surviving proportion (no events) at time t and shape, or
fail, t and shape: for the failure proportion (events) at time t and shape, or
intercept and scale: for values from a survreg regression

[ FAIL 0 | WARN 0 | SKIP 0 | PASS 131 ]
> 
> proc.time()
   user  system elapsed 
  37.75    1.70   39.43