weightedCL (version 0.5)

pbvt: BIVARIATE NORMAL AND STUDENT CDFs WITH VECTORIZED INPUTS

Description

Bivariate normal and Student cdfs with vectorized inputs

Usage

pbvt(z1,z2,param,icheck=FALSE)

Value

cdf value(s)

Arguments

z1

scalar or vector of reals

z2

scalar or vector of reals

param

vector of length 2, or matrix with 2 columns; vectors and number of rows of matrix cannot be different if larger than 1; for param, first column is rho, second column is df.

icheck

TRUE if checks are made for proper inputs, default of FALSE

References

Joe H (2014) CopulaModel: Dependence Modeling with Copulas. Software for book: Dependence Modeling with Copulas, Chapman & Hall/CRC, 2014.

Examples

cat("\n pbvt rho changing\n")
z1=.3; z2=.4; rho=seq(-.9,.9,.1); nu=2
param=cbind(rho,rep(nu,length(rho)))
out1=pbvt(z1,z2,param)
print(cbind(rho,out1))
cat("\n pbvt z1 changing\n")
z1=seq(-2,2,.4)
z2=.4; rho=.5; nu=2
out2=pbvt(z1,z2,c(rho,nu))
print(cbind(z1,out2))