coptrivmxid: Trivariate copula cdfs from mixture of max-id

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

Trivariate copula cdfs from mixture of max-id and bivariate (1,2) margin. These are functions for copula-based Markov order2 time series.

Usage

pmxid3ps(uu,param)   # positive stable LT and pfrk for H12,H32
pmxidr3ps(uu,param)  # reflected pmxid3ps
pmxid3ls(uu,param)   # log series LT and pfrk for H12,H32
ptmm1(uu,param)      # positive stable LT and pgum for H12,H32 (example of MM1)
pmxid2ps(u,v,param)  # bivariate (1,2) margin
pmxidr2ps(u,v,param)
pmxid2ls(u,v,param)
pbmm1(u,v,param)
pcondbmm1(v,u,param) # conditional cdf of pbmm1 with respect to u
dbmm1(u,v,param)     # density of pbmm1

Arguments

uu	vector of size 3 with numbers in (0,1) for trivariate copula
u	value in interval 0,1 for bivariate copula
v	value in interval 0,1 for bivariate copula
param	copula parameter =(LTpar,cpar12)

Value

cdf or pdf

Examples

u=seq(.1,.9,.2)
v=u
param=c(1.5,1.2)
pmxid2ps(u,v,param)  
pmxidr2ps(u,v,param)  
pmxid2ls(u,v,param)  
pbmm1(u,v,param)  
pcondbmm1(v,u,param)  
uu=c(.1,.4,.6)
pmxid3ps(uu,param)  
pmxidr3ps(uu,param)  
pmxid3ls(uu,param)  
ptmm1(uu,param)  

YafeiXu/CopulaModel documentation built on May 9, 2019, 11:07 p.m.