Changes in version 0.1.2 (2025-08-31)

* Constrained optimization now possible via nlminb.
* Censoring of non-final observations possible for misclassification models.
* Left truncation possible for misclassification models.
* Introduced informative observation testing via inform option.
* The control argument can now be a named list rather than a nhm.control object.
* Phase-type semi-Markov models can be accommodated for "bespoke" type models using the phasemap option.
* Parallel computing also now used for performing the forward algorithm for misclassification models and to calculate the Hessian using finite differences .
* Links to functions in other packages fixed within help documentation.

Changes in version 0.1.1 (2023-11-02)

* Fixed bug in model.nhm that occurred if a bespoke model was specified without including the number of parameters as an attribute in the intens function.
* Fixed bug in ematrix.nhm when a null covvalue is supplied.
* Fixed an error in the way in which individual component-wise p-values are calculated for the score test (in print.nhm_score). The vignette has also been updated to give correct results for the example.
* Fixed bug when a model of Weibull type is specified with no time-dependent terms.
* Fixed bug in dataprocess.nhm that occurred if a model with covariates and estimated initp was specified with firstobs="misc" (thanks to Emmett Kendall for the report).