pcondcop {CopulaREMADA} | R Documentation |
Bivariate copula conditional distribution functions
Description
Bivariate copula conditional distribution functions
Usage
pcondbvn(v,u,cpar)
pcondfrk(v,u,cpar)
pcondcln(v,u,cpar)
pcondcln90(v,u,cpar)
pcondcln270(v,u,cpar)
Arguments
v |
conditioning value in interval 0,1; could be a vector |
u |
value in interval 0,1; could be a vector |
cpar |
copula parameter: scalar. |
Details
Choices appending 'cop' are bvn, frk, cln, cln90 (rotated by 90 degrees cln), cln180 (rotated by 180 degrees cln), cln270 (rotated by 270 degrees cln).
See help page for dcop
for the abbreviations of the copula names.
Value
inverse conditional cdf value(s)
References
Joe H (1997) Multivariate Models and Dependence Concepts. Chapman & Hall
Joe H (2014) Dependence Modeling with Copulas. Chapman & Hall/CRC.
Joe H (2014) CopulaModel: Dependence Modeling with Copulas. Software for book: Dependence Modeling with Copulas, Chapman & Hall/CRC, 2014.
See Also
[Package CopulaREMADA version 1.6.2 Index]