dbvn: bivariate normal (Gaussian) and t densities

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

bivariate normal (Gaussian) and t densities, and logarithm of densities

Usage

dbvn(x,rho)
dbvn2(x1,x2,rho)
logdbvn(x1,x2,rho)
dbvt(x1,x2,param,log=FALSE)

Arguments

x	2-dimensional vector
x1	scalar or vector
x2	scalar or vector
rho	correlation in (-1,1)
param	(rho,nu) with rho in (-1,1) and nu>0
log	T to return log density, =F to return density

Value

bivariate normal density (could be vector for dbvn2 if one or more of x1,x2,rho is a vector)

Examples

dbvn(c(1,.5),.5)
dbvn2(seq(.2,1,.2),seq(.1,.5,.1),.5)
dbvt(1,.5,c(.5,50))
jpdf=dbvt(1,.5,c(.5,5))
dbvt(1,.5,c(.5,5),log=TRUE)
log(jpdf)

YafeiXu/CopulaModel documentation built on May 9, 2019, 11:07 p.m.