CopulaFamiliesCDF {HMMcopula} | R Documentation |
CopulaFamiliesCDF
Description
COPULACDF Cumulative probability function for a copula with linear correlation parameters RHO
Usage
CopulaFamiliesCDF(family, u, ...)
Arguments
family |
copula familly= "gaussian" , "t" , "clayton" , "frank" , "gumbel" |
u |
is an N-by-P matrix of values in [0,1], representing N points in the P-dimensional unit hypercube |
... |
additionnal parameter like RHO a P-by-P correlation matrix. |
Value
Y = COPULACDF('Gaussian',U,RHO) returns the cumulative probability of the Gaussian copula with linear correlation parameters RHO, evaluated at the points in U. U is an N-by-P matrix of values in [0,1], representing N points in the P-dimensional unit hypercube. RHO is a P-by-P correlation matrix. If U is an N-by-2 matrix, RHO may also be a scalar correlation coefficient.
Y = COPULACDF('t',U,RHO,NU) returns the cumulative probability of the t copula with linear correlation parameters RHO and degrees of freedom parameter NU, evaluated at the points in U. U is an N-by-P matrix of values in [0,1]. RHO is a P-by-P correlation matrix. If U is an N-by-2 matrix, RHO may also be a scalar correlation coefficient.
Y = COPULACDF(FAMILY,U,ALPHA) returns the cumulative probability of the bivariate Archimedean copula determined by FAMILY, with scalar parameter ALPHA, evaluated at the points in U. FAMILY is 'Clayton', 'Frank', ort 'Gumbel'. U is an N-by-2 matrix of values in [0,1].
Examples
u = seq(0,1,0.1);
U1=matrix(rep(u,length(u)),nrow=length(u),byrow = TRUE); U2=t(U1)
F = CopulaFamiliesCDF('clayton',cbind(c(U1), c(U2)),1)