As stated above, you can use the survreg function. A note though: this is not strictly a Cox PH model, but rather location-scale models. Using the default log-transformation, this is the aft model. In the case of the exponential distribution, the proportional hazards and aft model are equivalent, so if distribution is set to exponential, this is a proportional hazards model with an exponential baseline. Likewise, if a baseline Weibull distribution aft model is used, the parameter estimates are just a linear transformation of those used in the proportional hazards model
with Weibull baseline distribution. But in general, survreg does not fit a Cox PH model.
If a semi-parametric model is desired, as found implemented in intcox, a word of caution: there are several issues with the current version of intcox (algorithm typically prematurely terminates significantly far from the MLE, fails outright with uncensored observations, no standard errors automatically presented).
A new alternative that you could use is the package "icenReg".
Admission of bias: this is the author of icenReg.
intcox
package even if it's not onCRAN
using the normalinstall.packages("intcox")
. $\endgroup$ – smillig Dec 12 '12 at 15:23install.packages("intcox")
without any particular trouble (R-devel, but any modern R should work) $\endgroup$ – Ben Bolker Dec 21 '14 at 21:41