CIARphikalman: Minus Log Likelihood of the CIAR Model

In iAR: Irregularly Observed Autoregressive Models

Minus Log Likelihood of the CIAR Model

Description

This function return the negative log likelihood of the CIAR process given specific values of phiR and phiI

Usage

CIARphikalman(yest, x, y, t, yerr, zeroMean = TRUE, standardized = TRUE, c = 1)

Arguments

yest	The estimate of a missing value in the time series. This function recognizes a missing value with a NA. If the time series does not have a missing value, this value does not affect the computation of the likelihood.
x	An array with the parameters of the CIAR model. The elements of the array are, in order, the real (phiR) and the imaginary (phiI) part of the coefficient of CIAR model.
y	Array with the time series observations.
t	Array with the irregular observational times.
yerr	Array with the measurements error standard deviations.
zeroMean	logical; if TRUE, the array y has zero mean; if FALSE, y has a mean different from zero.
standardized	logical; if TRUE, the array y is standardized; if FALSE, y contains the raw time series.
c	Nuisance parameter corresponding to the variance of the imaginary part.

Value

Value of the negative log likelihood evaluated in phiR and phiI.

References

\insertRef

Elorrieta_2019iAR

See Also

gentime, CIARsample

Examples

n=300
set.seed(6714)
st<-gentime(n)
x=CIARsample(n=n,phiR=0.9,phiI=0,st=st,c=1)
y=x$y
yerr=rep(0,n)
CIARphikalman(x=c(0.8,0),y=y,t=st,yerr=yerr,yest=0)

iAR documentation built on Nov. 25, 2022, 1:06 a.m.