# 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

