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tramME 1.0.5 (2023-06-28)

• Refactor code, clean up documentation, unexport internal functions.
• Improve numerical robustness (log-likelihood, edf).

tramME 1.0.4 (2023-04-04)

• Activate the multi-core capabilities of TMB
• Resp() function to extend the functionality of Surv objects
• trafo option for plot.smooth.tramME to plot monotonic transformations of the smooth terms
• Faster and more robust vcov and edf_smooth calculations.
• simulate method (with limited functionality in this version) returned
• Updated additive tramME package vignette

tramME 1.0.3 (2022-09-05)

• Adapted matrix type conversions to Matrix 1.5.0.
• Fixed typo in vignette mixed-effects-additive-models.

tramME 1.0.2 (2022-07-04)

• Updated vignette mixed-effects-additive-models.
• Cleaned up the documentation.

tramME 1.0.1 (2022-04-23)

• Updated test utilities to avoid issues with MKL on CRAN.

tramME 1.0.0 (2022-04-12)

• Smooth shift terms as defined by mgcv. Currently only s() smooths are allowed.
• Cleaned up the source code and the documentation.
• The official reference is Tamasi and Hothorn (2021), vignette was also updated.
• New vignette with examples of mixed-effects transformation models with smooth shift terms.
• Some methods have been moved to development branch for proper testing and refactoring (Aareg, lpterms, simulate, parboot, trafo). These features may eventually find their way back to the package, probably in a slightly changed form.

tramME 0.1.3 (2022-03-08)

• Fixed duplicate.tramTMB method to work with TMB 1.8.0.

tramME 0.1.2 (2021-08-16)

• Added R-Forge URL

tramME 0.1.1 (2021-04-05)

• Fixed uninitialized value problem indicated by valgrind

tramME 0.1.0 (2021-03-29)

• Updated internal functions for estimation transformation models with TMB:
  • Fixed effects only models can be estimated
  • Exported functions (coef, logLik) communicate with the TMB model more smoothly
  • Updated internal structure to help future development (not exported currently)
• Fixing coefficients with the argument fixed = c(name = value)
• New model classes in SurvregME using the parameter fixing option
• AaregME extends the (parametric) Aalen regression model of tram with mixed-effects.
• Out-of-sample log-likelihoods using the newdata argument of logLik
• Score residuals with the resid method. When frequently recalculated (e.g. in boosting), setting resid = TRUE in model definition increases efficiency.
• Updating models via the update method
• Setting observation weights and offsets efficiently (activated with do_update = TRUE). Currently, only possible through directly manipulating the tmb_obj of the model.
• Parametric bootstrap with the parboot method
• New optimization options (e.g. internal scaling of fixed effects design matrix to improve convergence, more sensible initial values) and improved control over the optimization process with optim_control()
• Various methods (including analytical in the case of fixed effects only models) to calculate the Hessian; trying harder to invert the Hessian in numerically unstable cases.
• Calculate the linear predictor with type = "lp" in predict
• Several additional methods to help the user working with tramME objects: model.frame, model.matrix, fitmod, duplicate.
• Improved unit testing
• Improved documentation
• Demo for IPD meta-analysis

tramME 0.0.4 (2021-02-04)

• fixed bug in setting error distributions of ‘dummy’ ctms for predict and simulate methods
• updated Figure 6 in vignette, because the bug above affected predict in the case of CorlME
• fixed bug in unit test for simulate that caused error with mlt 1.2-1
• fixed simulate output structure with what = "joint" option

tramME 0.0.3 (2020-07-30)

• Added author ORCID
• Fixed CRAN issue with unit test using MKL
• Figure 3 color/legend changed in Vignette

tramME 0.0.2 (2020-03-30)

• Fixed numerical precision problem in unit tests

tramME 0.0.1 (2020-03-20)

• First CRAN version

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.