pfcm: The Distribution of Univariate Factor Copula Model

In eFCM: Exponential Factor Copula Model

The Distribution of Univariate Factor Copula Model

Description

Density, distribution function, quantile function and random generation for the distribution of univariate factor copula model with rate parameter equal to lambda.

Usage

pfcm(w, lambda)

dfcm(w, lambda)

qfcm(u, lambda, tol = 1e-08, niter = 1000L)

rfcm(n, lambda)

Arguments

w	A numeric value representing the spatial process.
lambda	A numeric value representing rate parameter \lambda.
u	a numeric vector of probabilities, with values in the interval from 0 to 1, at which the quantile function is to be computed.
tol	a scalar indicating the desired level of numerical accuracy for the algorithm; default is 1e-9.
niter	a scalar indicating the maximum number of iterations.
n	an integer value specifying the number of samples to generate

Details

The univariate eFCM distribution is

F(w;\lambda)=\Phi(w)-exp(\lambda^2/2-\lambda w)\Phi(w-\lambda),

where \lambda is the rate parameter.

Value

dfcm gives a numeric value representing the density of the factor copula model evaluated at w, pfcm gives a numeric value representing the CDF evaluated at w, qfcm gives the quantile function (QF) of the factor copula model. and rfcm generate a numeric vector of random samples drawn.

Examples

pfcm(w = 1, lambda = 0.5)
dfcm(w = 1, lambda = 0.5)
qfcm(u = 0.5, lambda = 0.5)
rfcm(n = 1000, lambda = 0.5)

eFCM documentation built on Sept. 9, 2025, 5:52 p.m.