Hello,
I am not seeing errors, except that you haven't posted the code for
pbivnorm. Do you have a variable named T somewhere? Don't abbreviate
TRUE to T in more complex code. Or FALSE to F.
And both functions mycdf and mycdf2 could be simplified.
mycdf <- function(q,logistic=FALSE){
# *********************************************
# Univariate CDF: normal or logistic
# *********************************************
if(!logistic){
pnorm(q)
} else {
plogis(q)
}
}
mycdf2 <- function(x,y,rho,logistic=FALSE){
# *********************************************
# Calling bivariate CDF: normal or logistic
# *********************************************
if(!logistic){
pbivnorm(x,y,rho,recycle=TRUE)
} else {
pbivlogis(x,y,rho)
}
}
As one-liners:
mycdf <- function(q,logistic=FALSE){
# *********************************************
# Univariate CDF: normal or logistic
# *********************************************
if(logistic) plogis(q) else pnorm(q)
}
mycdf2 <- function(x,y,rho,logistic=FALSE){
# *********************************************
# Calling bivariate CDF: normal or logistic
# *********************************************
if(logistic) pbivlogis(x,y,rho) else pbivnorm(x,y,rho,recycle=TRUE)
}
Hope this helps,
Rui Barradas
?s 06:14 de 25/01/21, Steven Yen escreveu:> Dear All
>
> Below are calls to functions to calculate bivariate and univariate
> logistic probabilities.It works for the following sample program (with
> results p1=p2 and p3=p4), but similar calls in a more elaborated program
> produced unpredicted results.
>
> My question is whether I am doing something bad (which I should avoid)
> in my calls to mycdf2 and mycdf to obtain p2 and p3, respectively. Thank
> you.
>
> Steven Yen
>
> pbivlogis <- function(x,y,rho){
> # *********************************************
> # Bivariate logistic CDF
> # *********************************************
> ? p<-(1+exp(-x)+exp(-y)+(1-rho)*exp(-x-y))^(-1)
> return(p)
> }
>
> mycdf <- function(q,logistic=FALSE){
> # *********************************************
> # Univariate CDF: normal or logistic
> # *********************************************
> ? if(!logistic){
> ??? p<-pnorm(q)
> ? } else {
> ??? p<-plogis(q)
> ? }
> return(p)
> }
>
> mycdf2 <- function(x,y,rho,logistic=FALSE){
> # *********************************************
> # Calling bivariate CDF: normal or logistic
> # *********************************************
> ? if(!logistic){
> ??? p<-pbivnorm(x,y,rho,recycle=T)
> ? } else {
> ??? p<-pbivlogis(x,y,rho)
> ? }
> return(p)
> }
>
> set.seed(123)
> x<-runif(n=5,min=-3,max=3)
> y<-runif(n=5,min=-2,max=4)
> rho<-0.5
>
> p1<-pbivlogis(x,y,rho); p1
> p2<-mycdf2(x,y,rho,logistic=TRUE); p2
>
> p3<-mycdf(x,logistic=T); p3
> p4<-plogis(x); p4
>
> Results
>
> > set.seed(123)
> > x<-runif(n=5,min=-3,max=3)
> > y<-runif(n=5,min=-2,max=4)
> > rho<-0.5
> > p1<-pbivlogis(x,y,rho); p1
> [1] 0.04937376 0.65977865 0.35821101 0.72243120 0.63881214
> > p2<-mycdf2(x,y,rho,logistic=TRUE); p2
> [1] 0.04937376 0.65977865 0.35821101 0.72243120 0.63881214
> > p3<-mycdf(x,logistic=T); p3
> [1] 0.2184819 0.8493908 0.3667608 0.9087199 0.9335661
> > p4<-plogis(x); p4
> [1] 0.2184819 0.8493908 0.3667608 0.9087199 0.9335661
> >
>
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