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summary.JointFPM()
, which provides a ncer
overview of the model estimatespredict.JointFPM()
includes new control
and ...
arguments, which are passed to
rstpm2::gms()
and can be used to control the estimation
procedure (pull request #12 by @ellessenne).predict.JointFP()
allows now to chose Gaussian
quadrature instead of Romberg’s method for the integration of the
production of the survival and intensity function for estimating the
mean number of events (@ellessenne, #8). Using Gaussian
quadrature is fast while providing results similar to Romberg’s method,
if a sufficient number if nodes is chosen. This might be particular
useful when standardising over linear covariates.JointFPM()
predict.JointFPM()
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They may not be fully stable and should be used with caution. We make no claims about them.