View source: R/hazard.smoothSurvReg.R
hazard.smoothSurvReg | R Documentation |
Compute and plot hazard function for given combinations of covariates based on the fitted model.
## S3 method for class 'smoothSurvReg' hazard(x, cov, logscale.cov, time0 = 0, plot = TRUE, by, xlim, ylim, xlab = "t", ylab = "h(t)", type = "l", lty, main, sub, legend, bty = "n", cex.legend = 1, ...)
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 number of covariates (interactions included). Intercept is not
to be included in |
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*epsilon |
plot |
If |
by |
Step for a ploting grid. If |
xlim, ylim |
Arguments passed to the |
xlab, ylab |
Arguments passed to the |
type, lty |
Arguments passed to the |
main, sub |
Arguments passed to the |
legend, bty |
Argument passed to the |
cex.legend |
argument passed to |
... |
Arguments passed to the |
A dataframe with columns named x
and y
where x
gives the grid
and y
the values of the hazard function at that grid.
Arnošt Komárek arnost.komarek@mff.cuni.cz
smoothSurvReg
, plot
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