Learn R Programming

smoothSurv (version 0.7)

fdensity.smoothSurvReg: Density for Objects of Class 'smoothSurvReg'

Description

Compute and plot density function for given combinations of covariates based on the fitted model.

Usage

## S3 method for class 'smoothSurvReg':
fdensity(x, cov, logscale.cov, time0 = 0, plot = TRUE,
    by, xlim, ylim, xlab = "t", ylab = "f(t)", 
    type = "l", lty, main, sub, legend, bty = "n", ...)

Arguments

x
Object of class smoothSurvReg.
cov
Vector or matrix with covariates values for which the survivor curve/cdf is to be computed and plotted. It must be a matrix with as many columns as is the number of covariates (interactions included) or the vector of length equal to the
logscale.cov
Vector or matrix with covariate values for the expression of log-scale (if this depended on covariates). It can be omitted in the case that log-scale was common for all observations.
time0
Starting time of the follow-up as used in the model. I.e. the model is assumed to be $\log(T-time0) = x'\beta + \sigma\varepsilon$
plot
If TRUE the plot is directly produced, otherwise only a data.frame with information used for later plotting is returned.
by
Step for a ploting grid. If missing it is automatically computed.
xlim, ylim
Arguments passed to the plot function.
xlab, ylab
Arguments passed to the plot function.
type, lty
Arguments passed to the plot function.
main, sub
Arguments passed to the plot function.
legend, bty
Argument passed to the plot function.
...
Arguments passed to the plot function.

Value

  • A dataframe with columns named x and y where x gives the grid and y the values of the density function at that grid.

See Also

smoothSurvReg, plot