MAP.continuous function

Estimation of latent variables in the continuous case

This function computes the estimation of a latent variables for each cluster using the conditional a posteriori median.

MAP.continuous(u, family, rot, thC0k, dfC = NULL, nq = 35)

Arguments

• u: vector of values in (0,1)
• family: copula family: "gaussian" , "t" , "clayton" , "joe", "frank" , "fgm", gumbel", "plackett", "galambos", "huesler-reiss"
• rot: rotation: 0 (default), 90, 180 (survival), or 270.
• thC0k: vector of copula parameters
• dfC: degrees of freedom for the Student copula (default is NULL)
• nq: number of nodes and weighted for Gaussian quadrature of the product of conditional copulas; default is 31.

Returns

• condmed: Conditional a posteriori median.

Examples

u = c(0.5228155, 0.3064417, 0.2789849, 0.5176489, 0.3587144)
thC0k=rep(17.54873,5)
MAP.continuous(u,"clayton",rot=90,thC0k,nq=35)

References

Krupskii, Nasri & Remillard (2023). On factor copula-based mixed regression models

Author(s)

Pavel Krupskii, Bouchra R. Nasri and Bruno N. Remillard