CIARphikalman {iAR} | R Documentation |
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
Elorrieta, F, Eyheramendy, S, Palma, W (2019). “Discrete-time autoregressive model for unequally spaced time-series observations.” A&A, 627, A120. doi: 10.1051/0004-6361/201935560, https://doi.org/10.1051/0004-6361/201935560.
See Also
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)