copulaIVTS-package: Gaussian copula model for Integer-valued Time series -...

In hlennon/copulaIVTS: Dependence modelling of a digitised Gaussian ARMA(p,q) copula model for Integer-Valued Time Series

Description

The R package copulaIVTS provides all statistical R used to implement a Monte Carlo Expectation Maximisation algorithm for maximum likelihood estimation of the dependence parameters of a digitised Gaussian ARMA model. Useful for count time series also.

Monte Carlo EM algorithm Code. Code to run the Monte Carlo EM algorithm for parameter estimation of the Gaussian copula model with specified discrete marginals.

To be be added to the R package shortly are two alternative estimation methods to fit the digitised Gaussian ARMA model provided in the Thesis link via Approximate Bayesian Computation (ABC) and via approximate MLE via a d-vine bivariate copula representation.

Details

Package:	copulaIVTS
Type:	Package
Version:	1.2
Date:	2021-03-23
License:	GPL (>=2)

Author(s)

Hannah Lennon <[e-mail]>

References

Lennon H., & Yuan J., Estimation of a digitised Gaussian ARMA model by Monte Carlo Expectation Maximisation, Computational Statistics & Data Analysis 2018;8:e020683

Lennon, H., 2016. Gaussian copula modelling for integer-valued time series (Doctoral Thesis, University of Manchester).

hlennon/copulaIVTS documentation built on Dec. 20, 2021, 4:45 p.m.