survReg.
survReg function.
dsurvReg(x, mean, scale=1, distribution='weibull') psurvReg(q, mean, scale=1, distribution='weibull') qsurvReg(p, mean, scale=1, distribution='weibull')
NAs) are allowed.
NAs) are allowed.
NAs) are allowed.
p
or
q.
p
or
q.
survReg.distributions
dsurvReg),
probability (
psurvReg),
quantile (
qsurvReg), or
for the requested distribution with mean and scale
parameters
mean and
sd
.
Elements of
q or
p
that are missing will cause the corresponding
elements of the result to be missing.
The
mean and
scale
values are as they would be for
survReg.
In particular, if
the distribution is one that involves a transformation, then they are the
mean and scale of the transformed distribution.
For example, the Weibull distribution is fit using the
Extreme value distribution along with a log transformation.
Letting F(t) = 1 - exp(-(at)^p) be the cumulative distribution of the
Weibull, the mean corresponds to -log(a) and the scale to 1/p
(Kalbfleisch and Prentice, 1980, section 2.2.2).
Kalbfleisch, J. D. and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data Wiley, New York.
# List of distributions available names(survReg.distributions) # Shows: # [1] "extreme" "logistic" "gaussian" "weibull" "exponential" # [6] "rayleigh" "loggaussian" "lognormal" "loglogistic" "t" # Compare results all.equal(dsurvReg(1:10, 2, 5, dist='lognormal'), dlnorm(1:10, 2, 5)) # Hazard function for a Weibull distribution x <- seq(0.1, 3, length=30) haz <- dsurvReg(x, 2, 3)/(1-psurvReg(x, 2, 3)) plot(x, haz, log='xy', ylab="Hazard") # line with slope (1/scale - 1)