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by John Aponte
This package defines a set of classes that encapsulate survival distributions
The objects of the class SURVIVAL encapsulate distributions of survival times. Each class has its own set of parameters but once the SURVIVAL object is defined, they have access to the same functions to calculate:
survival time function: sfx()
,
hazard time function: hfx()
,
cumulative hazard function: Cum_Hfx()
the inverse of the cumulative hazard function:
invCum_Hfx()
.
generate random survival times: rsurv()
generate random survival times under proportional hazard ratio:
rsurvhr()
.
generate random survival times under accelerated failure :
rsuvrvaft()
generate random survival times under accelerate hazard:
rsurvah()
There are several functions to plot the distributions
generic S3: plot.SURVIVAL()
plot_survival()
: to plot the functions
ggplot_survival_random()
: to ggplot random draws
from the distribution
ggplot_survival_hr()
: to ggplot random draws from
the distribution using hazard ratio
ggplot_survival_aft()
: to ggplot random draws from
the distribution using accelerated time failure
ggplot_survival_ah()
: to ggplot random draws from
the distribution using accelerated hazard
compare_survival()
: to graphically compare the
functions of two SURVIVAL objects
The current factories are implemented:
s_exponential()
: for Exponential
distributions
s_weibull()
: for Weibull distributions
s_gompertz()
: for Gompertz distributions
s_piecewise()
: for Piecewise exponential
distributions
s_loglogistic()
: for Log Logistic
distributions
s_lognormal()
: for Log Normal distributions
See the vignettes for examples on the use on simulation of survival data.
To install the development version of this package from github use:
devtools::install_github("johnaponte/survobj", build_manual = T, build_vignettes = T)
For more information:
https://johnaponte.github.io/survobj/
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.