IARginterpolation: Interpolation from IAR-Gamma model

In iAR: Irregularly Observed Autoregressive Models

Interpolation from IAR-Gamma model

Description

Interpolation of missing values from models fitted by IARgamma

Usage

IARginterpolation(x, y, st, yini = 1)

Arguments

x	A given array with the parameters of the IAR-Gamma model. The first element of the array corresponding to the phi parameter, the second to the level parameter mu, and the last one to the scale parameter sigma.
y	Array with the time series observations.
st	Array with the irregular observational times.
yini	a single value, initial value for the estimation of the missing value of the time series.

Value

A list with the following components:

• fitted Estimation of a missing value of the IAR-Gamma process.

• ll Value of the negative log likelihood evaluated in the fitted missing values.

References

\insertRef

Eyheramendy_2018iAR

See Also

gentime, IARgsample, IARgamma

Examples

set.seed(6714)
n<-100
st<-gentime(n)
y<-IARgsample(phi=0.9,st=st,n=n,sigma2=1,mu=1)
model<-IARgamma(y$y, st=st)
y<-y$y
napos=10
y0=y
y[napos]=NA
xest=c(model$phi,model$mu,model$sigma)
yest=IARginterpolation(x=xest,y=y,st=st)
yest$fitted
mse=(y0[napos]-yest$fitted)^2
print(mse)
plot(st,y,type='l',xlim=c(st[napos-5],st[napos+5]))
points(st,y,pch=20)
points(st[napos],yest$fitted,col="red",pch=20)

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