copula2d.cond: Some Parametric Conditional Bivariate Copulas

In mable: Maximum Approximate Bernstein/Beta Likelihood Estimation

Some Parametric Conditional Bivariate Copulas

Description

Density, distribution function, quantile function and random generation for conditional copula C(u|V=v) of U given V=v related to parametric bivariate copula C(u,v)=P(U\le u, V\le v).

Usage

dcopula.cond(u, v, copula, ...)

pcopula.cond(u, v, copula, ...)

qcopula.cond(p, v, copula, ...)

rcopula.cond(n, v, copula, ...)

Arguments

u	vector of U values at which the copula density is evaluated
v	a given value of V under which the conditional copula and its density is evaluated
copula	the name of a copula density to be called (see Details)
...	the parameter(s) of copula
p	a vector of probabilities
n	number of observations to be generated from conditional copula C(u|V=v).

Details

the names of available copulas are 'amh' (Ali-Mikhai-Haq), 'bern' (Bernstein polynomial model), 'clayton'(Clayton), 'exponential' (Exponential), 'fgm'(Farlie–Gumbel–Morgenstern), 'frank' (Frank), 'gauss' (Gaussian), 'gumbel' (Gumbel), 'indep' (Independence), 'joe' (Joe), 'nakagami' (Nakagami-m), 'plackett' (Plackett), 't' (Student's t).

Value

a vector of copula density values evaluated at u gvien V=v or a vector of n generated u values from conditional copula C(u|V=v).

mable documentation built on Oct. 1, 2024, 9:06 a.m.