JointFPM 1.3.0

• Stable release of mean_no function

JointFPM 1.2.2

• The DESCRIPTION file now includes a link to the article in the Biometrical Journal describing the method implemented in this package.
• The package now requieres R >= 4.1.0, due to the use of the native pipe operator. This fixes a note in the CRAN checks

JointFPM 1.2.1

• Added summary.JointFPM(), which provides a nicer overview of the model estimates
• predict.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).

JointFPM 1.2.0

• 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.
• Fixed a small error when upgrading to Roxygen 7.3.0 #10.

JointFPM 1.1.0

• Added standardization for estimating marginal estimates of the mean number of events and differences thereof
• Added checks of user inputs to JointFPM()
• Added checks of user inputs to predict.JointFPM()
• Improved error messages
• Improved testing coverage

JointFPM 1.0.1

• Fixed bug when calculating difference between two mean number of events functions
• Added tests for predict function

JointFPM 1.0.0

• First stable release