R/Dbvn.R In mets: Analysis of Multivariate Event Times

Documented in Dbvn

```##' Derivatives of the bivariate normal cumulative distribution function
##'
##' @title Derivatives of the bivariate normal cumulative distribution function
##' @param p Parameter vector
##' @param design Design function with defines mean, derivative of mean, variance,
##' and derivative of variance with respect to the parameter p
##' @param Y column vector where the CDF is evaluated
##' @author Klaus K. Holst
##' @usage
##' Dbvn(p,design=function(p,...) {
##'      return(list(mu=cbind(p[1],p[1]),
##'                dmu=cbind(1,1),
##'                S=matrix(c(p[2],p[3],p[3],p[4]),ncol=2),
##'                dS=rbind(c(1,0,0,0),c(0,1,1,0),c(0,0,0,1)))  )},
##'      Y=cbind(0,0))
##' @export
Dbvn <- function(p,design=function(p,...) {
return(list(mu=cbind(p[1],p[1]),
dmu=cbind(1,1),
S=matrix(c(p[2],p[3],p[3],p[4]),ncol=2),
dS=rbind(c(1,0,0,0),c(0,1,1,0),c(0,0,0,1)))
)},
Y=cbind(0,0)) {
mS <- design(p)
U0 <- with(mS,.Call("biprobit0",
mu,
S,dS,Y,dmu,NULL,FALSE));
return(c(U0,mS))
}
```

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mets documentation built on May 31, 2017, 1:52 a.m.