IARgamma {iAR}

Maximum Likelihood Estimation of the IAR-Gamma model

Description

Maximum Likelihood Estimation of the IAR-Gamma model.

Usage

IARgamma(y, st)

Arguments

y

Array with the time series observations

st

Array with the irregular observational times

Value

A list with the following components:

• phi MLE of the phi parameter of the IAR-Gamma model.

• mu MLE of the mu parameter of the IAR-Gamma model.

• sigma MLE of the sigma parameter of the IAR-Gamma model.

• ll Value of the negative log likelihood evaluated in phi, mu and sigma.

References

Eyheramendy S, Elorrieta F, Palma W (2018). “An irregular discrete time series model to identify residuals with autocorrelation in astronomical light curves.” Monthly Notices of the Royal Astronomical Society, 481(4), 4311–4322. ISSN 0035-8711, doi: 10.1093/mnras/sty2487, https://academic.oup.com/mnras/article-pdf/481/4/4311/25906473/sty2487.pdf.

See Also

gentime, IARgsample, IARphigamma

Examples

n=300
set.seed(6714)
st<-gentime(n)
y<-IARgsample(phi=0.9,st=st,n=n,sigma2=1,mu=1)
model<-IARgamma(y$y, st=st)
phi=model$phi
muest=model$mu
sigmaest=model$sigma