version 0.2-6.7
- Small bug fixed in an internal function. Thanks to Mateus Maia Marques.
- joint model with survival and binary outcomes.
- AT function now called ATE and various argument names modified for clarity.
- surv argument in gjrm() and gamlss() removed as survival models can be identified by the margins chosen.

version 0.2-6.6
- ordinal argument in gjrm() removed as the ordinal models can be identified by the margins chosen.
- Poisson is now "P" instead of "PO".
- gamlssfit is now uni.fit in gjrm().


version 0.2-6.5
- ordinal model summary fixed. 
- jc.probs now is copula.prob.
- hazsurv.plot now is hazsurv.

version 0.2-6.4
- speed of trivariate binary models improved. 

version 0.2-6.3
- better names used for arguments relating the copula functions. 

version 0.2-6.2
- ordinal model improved.

version 0.2-6.1
- bug in summary function fixed. Thanks to Trevor Fitzpatrick.
- models with ordinal margins implemented.

version 0.2-6
- extended class of ROY models implemented and final checks completed.
- copula survival models with general censoring scheme.

version 0.2-5.1
- Extended class of ROY models implemented.

version 0.2-5
- DGP0 distribution introduced.

version 0.2-4
- excess survival models implemented.
- Tweedie distribution allowed for.

version 0.2-3
- function for fitting linear models with positivity and sum-to-one constraints; see lmc().
- generalized Pareto and discrete generalized Pareto distributions implemented for univariate modelling.
- robust gamlss implemented.

version 0.2-2
- copula models with ordinal and continuous responses implemented.
- univariate survival models with mixed censoring implemented. 

version 0.2-1
- survival models with informative censoring.
- models now estimate sigma instead of sigma2.
- calculation for LN distribution in pred.mvt() fixed. Thanks to Maike Hohberg.

version 0.2
- copula survival models.
- copula models with binary and discrete margins.

version 0.1-5
- various bugs fixed and more models introduced.

version 0.1-4
- sample selection models with all types of marginal distributions allowed for.
- pred.mvt function to calculate covariate effects on the real scale.

version 0.1-3
- summary function for bivariate binary models fixed.
- jc.probs() extended to include calculation of tau and intervals.
- vis.gjrm funcion extended.

version 0.1-2
- all fitting functions merged and included in gjrm().
- manual updated.

version 0.1-1
- initial release of GJRM which is the continuation of SemiParBIVProbit.