IARt {iAR}

Maximum Likelihood Estimation of the IAR-T model

Description

Maximum Likelihood Estimation of the IAR-T model.

Usage

IARt(y, st, nu = 3)

Arguments

y

Array with the time series observations

st

Array with the irregular observational times

nu

degrees of freedom

Value

A list with the following components:

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

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

• ll Value of the negative log likelihood evaluated in phi 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, IARtsample, IARphit

Examples

n=300
set.seed(6714)
st<-gentime(n)
y<-IARtsample(n,0.9,st,sigma2=1,nu=3)
model<-IARt(y$y, st=st)
phi=model$phi
sigmaest=model$sigma