Multivariate Ordinal Regression Models

A flexible framework for fitting multivariate ordinal regression models with composite likelihood methods.


This file documents updates and changes in the package mvord

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

Reference manual

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0.3.2 by Rainer Hirk, 17 days ago

Browse source code at

Authors: Rainer Hirk [aut, cre] , Kurt Hornik [aut] , Laura Vana [aut] , Alan Genz [ctb] (Fortran Code)

Documentation:   PDF Manual  

GPL-3 license

Imports MASS, pbivnorm, stats, optimx, mnormt, numDeriv, Matrix

Depends on minqa, BB, ucminf, dfoptim

Suggests knitr

See at CRAN