estcontord: Estimating based on a bivariate sample of the multivariate...

In GenOrd: Simulation of Discrete Random Variables with Given Correlation Matrix and Marginal Distributions via a Gaussian or Student's t Copula

Estimating based on a bivariate sample of the multivariate latent standard normal or Student's t distribution

Description

Limited to the bivariate case, based on an iid sample, the function estimates the parameters of the t-copula-based discrete distribution, according to either a two-step approach (suggested) where the only unknown parameters are the copula correlation and the degrees of Freedom, whereas the marginal probabilities are estimated via the ecdf, or a full-maximum-likelihood approach, where also the two marginal probabilities are estimated jointly with the correlation and degrees of freedom

Usage

estcontord(x, method="2-step")

Arguments

x	a matrix with two columns containing integer values; it is the bivariate iid sample
method	"2-step" for estimating rho and df parametrically, and the margins via the ecdf; otherwise, a full-maximum-likelihood approach is carried out, where the marginal probabilities of the two random components are estimated as well

Value

a list containing the estimates and for the "2-step" method their standard errors

Author(s)

Alessandro Barbiero, Pier Alda Ferrari

See Also

ordcont,contord, ordsample, corrcheck

Examples

## not run
#x1 <- c(rep(0,223),rep(1,269),rep(2,8))
#x2 <- c(rep(0,153), rep(1,70), rep(0,75),rep(1,187),
#        rep(2,7),rep(0,2),rep(1,4),rep(2,2))
#cor(x1,x2)
#x<-cbind(x1,x2)
#res <- estcontord(x)
#res

GenOrd documentation built on Nov. 5, 2025, 7:31 p.m.