R/lava.tobit-package.R

In kkholst/lava.tobit: Latent Variable Models with Censored and Binary Outcomes

##' Estimation and simulation of probit and tobit latent variable models
##'
##' Framwork for estimating parameters and simulate data from Latent Variable
##' Models with binary and censored observations. Plugin for the \code{lava}
##' package
##'
##' \tabular{ll}{ Package: \tab lava.tobit \cr Type: \tab Package \cr Version:
##' \tab 0.4-5 \cr Date: \tab 2012-03-15 \cr License: \tab GPL-3 \cr LazyLoad:
##' \tab yes \cr }
##'
##' @name lava.tobit
##' @aliases lava.tobit lava.tobit-package
##' @docType package
##' @author Klaus K. Holst Maintainer: <kkho@@biostat.ku.dk>
##' @import lava mvtnorm survival
##' @keywords package
##' @examples
##'
##' library('lava.tobit')
##' m <- lvm(list(c(y,z) ~ x, y~z))
##' ## Simulate 200 observation from path analysis model
##' ## with all slopes and residual variances set to 1 and intercepts 0:
##' d <- sim(m,200,seed=1)
##' ## Dichotomize y and introduce censoring on z
##' d <- transform(d, y=as.factor(y>0), z=Surv(z,z<2))
##'
##' ##  if (requireNamespace("mets",quietly=TRUE)) {
##' ##    e <- estimate(m,d,control=list(trace=1),estimator="gaussian")
##' ##    effects(e,y~x)
##' ##  }
##'
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##' For internal use
##'
##' @title For internal use
##' @name lava.tobit.init.hook
##' @rdname internal
##' @aliases tobit_gradient.lvm tobit_hessian.lvm tobit_logLik.lvm
##' tobit_method.lvm tobit_objective.lvm tobitw_gradient.lvm tobitw_hessian.lvm
##' tobitw_method.lvm lava.tobit.color.hook
##' lava.tobit.init.hook lava.tobit.sim.hook
##' @author Klaus K. Holst
##' @keywords utilities
##' @export
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