Clayton.Markov.DATA.binom: Generating Time Series Data Under a Copula-Based Markov Chain...

In Copula.Markov: Copula-Based Estimation and Statistical Process Control for Serially Correlated Time Series

Description

Time-series data are generated under a copula-based Markov chain model with the Clayton copula and binomial margin.

Usage

Clayton.Markov.DATA.binom(n, size, prob, alpha)

Arguments

n	number of observations
size	number of binomial trials
prob	binomial probability; 0<p<1
alpha	association parameter

Details

-1<alpha<0 for negative association; alpha>0 for positive association

Value

Time series data of size n (this is different from the number of binomial trials = "size").

Author(s)

Huang XW, Chen W, Emura T

References

Chen W (2018) Copula-based Markov chain model with binomial data, NCU Library

Huang XW, Emura T (2021-), Computational methods for a copula-based Markov chain model with a binomial time series, in review

Examples

size=50
prob=0.5
alpha=2
set.seed(1)
Y=Clayton.Markov.DATA.binom(n=500,size,prob,alpha)
### sample mean and SD ###
mean(Y)
sd(Y)
### true mean and SD ###
size*prob
sqrt(size*prob*(1-prob))

Copula.Markov documentation built on Nov. 29, 2021, 9:07 a.m.