Joe.Markov.DATA {Copula.Markov}

Generating Time Series Data Under a Copula-Based Markov Chain Model with the Joe Copula

Description

Time-series data are generated under a copula-based Markov chain model with the Joe copula.

Usage

Joe.Markov.DATA(n, mu, sigma, alpha)

Arguments

n

sample size

mu

mean

sigma

standard deviation

alpha

association parameter

Details

alpha>=1 for positive association

Value

Time series data of size n

Author(s)

Takeshi Emura

References

Emura T, Long TH, Sun LH (2017), R routines for performing estimation and statistical process control under copula-based time series models, Communications in Statistics - Simulation and Computation, 46 (4): 3067-87

Long TS and Emura T (2014), A control chart using copula-based Markov chain models, Journal of the Chinese Statistical Association 52 (No.4): 466-96

Examples

n=1000
alpha=2.856 ### Kendall's tau =0.5 ###
mu=2
sigma=1
Y=Joe.Markov.DATA(n,mu,sigma,alpha)
mean(Y)
sd(Y)
cor(Y[-1],Y[-n],method="kendall")

Joe.Markov.MLE(Y,k=2)