IARforecast: Forecast from IAR model

In iAR: Irregularly Observed Autoregressive Models

Forecast from IAR model

Description

Forecast from models fitted by IARloglik

Usage

IARforecast(phi, y, st, standardized = TRUE, zero.mean = TRUE, tAhead)

Arguments

phi	Estimated phi parameter by the iAR model.
y	Array with the time series observations.
st	Array with the irregular observational times.
standardized	logical; if TRUE, the array y is standardized; if FALSE, y contains the raw time series
zero.mean	logical; if TRUE, the array y has zero mean; if FALSE, y has a mean different from zero.
tAhead	The time ahead for forecast is required.

Value

Forecasted value from the iAR model

References

\insertRef

Eyheramendy_2018iAR

See Also

gentime, IARsample, IARloglik, IARkalman, IARfit

Examples

set.seed(6714)
st<-gentime(n=100)
y<-IARsample(phi=0.99,st=st,n=100)
y<-y$series
n=length(y)
p=trunc(n*0.99)
ytr=y[1:p]
yte=y[(p+1):n]
str=st[1:p]
ste=st[(p+1):n]
tahead=ste-str[p]
phi=IARloglik(y=ytr,st=str)$phi
forIAR=IARforecast(phi=phi,y=ytr,st=str,tAhead=tahead)

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