copulaFamiliesPDF: COPULAPDF Probability density function for a copula....

In HMMcopula: Markov Regime Switching Copula Models Estimation and Goodness of Fit

Description

COPULAPDF Probability density function for a copula.

COPULAPDF probability density function for a copula with linear correlation parameters RHO and

Usage

copulaFamiliesPDF(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 = COPULAPDF('Gaussian',U,RHO) returns the probability density 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 = COPULAPDF('t',U,RHO,NU) returns the probability density 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 = COPULAPDF(FAMILY,U,ALPHA) returns the probability density of the bivariate Archimedean copula determined by FAMILY, with scalar parameter ALPHA, evaluated at the points in U. FAMILY is 'Clayton', 'Frank', or '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 = copulaFamiliesPDF('clayton',cbind(c(U1), c(U2)),1)

HMMcopula documentation built on April 21, 2020, 9:05 a.m.