This file documents updates and changes in the package mvord

changes in version 1.2.1 (2024-01-10)
- fixed bugs from the change NCOL(NULL) returns 0 rather than 1 

changes in version 1.2.0 (2022-11-18)
- added essay_data to mvord datasets
- added a combis argument in mvord.control which allows the specification of the combinations to be used, if user does not want to use all. 
- for logit link replaced sadmvt with ... sadmvt cannot not handle dimension larger than d=20 
- fixed bug for standard error when threshold.coef are e.g., rep(1:3, 3).

changes in version 1.1.1 (2020-03-16)
- fixed bug for value0 with cor_ar1

changes in version 1.1.0 (2020-11-17)
- speed up in PL_fun - minimal changes in the 10+ decimal places for some specific lead to minimal deviations in the optimization results of the general purpose optimizers. In some cases more evaluation steps are needed.
- implementation of PL_fast
- fixed bug in vector constraints for coef

changes in version 1.0.2 (2020-08-31)
- fixed bug in prediction with categorial variables with newdata

changes in version 1.0.1 (2020-05-27)
- changes in checks due to new treatment when combining ordered factors in R 4.0.1.

changes in version 1.0.0 (2020-04-17)
- publication in Journal of Statistical Software

changes in version 0.3.6 (2019-09-22)
- fixed bug in thresholds checks for two binary responses

changes in version 0.3.5 (2019-03-06)
- added suppressWarnings(RNGversion("3.5.0")) in tests

changes in version 0.3.4 (2019-02-20)
- two additional arguments have been added to the error structures: value = numeric(0)
  (for initial values) and fixed = FALSE (for allowing the user to fix the parameters of the error structure to the values specified in argument
  value)
- efficiency improvements by using rep.int, paste0, seq_len, seq_along where possible

changes in version 0.3.3 (2018-10-30)
- fixed bug standard errors with threshold.constraints

changes in version 0.3.2 (2018-10-03)
- function polycor() for polychoric correlations is now available
- added packages minqa, BB, ucminf and dfoptim as dependencies

changes in version 0.3.1 (2018-06-12)
- out-of-sample predictions are now available
- additional examples are now available in an additional vignette

changes in version 0.3.0 (2018-05-03)
- new model design with multiple measurement objects MMO and MMO2 (former mvord2())
- removed function mvord2()
- removed argument scale (covariates are scaled internally for optimizer)
- fixed bug in standard errors with binary outcomes
- removed argument response.names (if specific ordering is desired this can be performed by an ordered factor for the multiple measurement index)
- additional input types are now applicable for ordinal response variables
- fixed bug trace
- control = mvord.control()
- additional checks
- new function name marginal_predict() (instead of marginal.predict())
- new function name joint_probabilities() (instead of get.prob()); type "class" instead of "class.max"
- new function name error_structure() (instead of get_error_struct())

changes in version 0.2.1 (2017-11-29)
- adapted predict(), get.prob(), marginal.predict()
- added contrasts as argument to mvord() and mvord2()
- fixed bug in VGAM design of coef.constraints
- changed internal design matrices

changes in version 0.2.0 (2017-11-10)
- implemented nobs.mvord()
- implemented vcov.mvord()
- implemented terms.mvord()
- implemented model.matrix.mvord()
- implemented fitted.mvord()
- implemented logLik.mvord()
- AIC() and BIC() are now available
- additional argument scale
- new (additional) design for coef.constraints in analogy to constraints in VGAM
- category-specific regression parameters
- additional argument offset
- new class "mvlink"
- implemented coef.constraints()
- logPL(), claic() and clbic() are not exported anymore. use logLik(), AIC() and BIC() instead.
- renamed cor_general, cor_ar1, cor_equi, cov_general
- implemented names_constraints()


changes in version 0.1.0 (2017-10-17)
- changed function name from multord() to mvord()
- changed function name from multord2() to mvord2()
- implemented predict function()
- implemented predict.marginal function()
- implemented get.prob function()
- changed link probit to mvprobit()
- changed link logit to mvlogit(df = 8L); default value of degrees of freedom is 8
- implemented a more flexible multivariate logistic distribution with logistic marginals and t copula (df are settable)
- additional argument PL.lag

