Hello,
This is cross-posted, you have posted the same question in SO[1].
Cross-posting is not well seen, post the question in one place and
please wait a few days for an answer before posting here.
[1]
https://stackoverflow.com/questions/64197235/forecasting-of-multivariate-data-through-vector-autoregression-model
Hope this helps,
Rui Barradas
Às 17:25 de 04/10/20, Faheem Jan via R-help escreveu:
Hello , i am working in the functional time series using themultivariate time
series data(hourly time series data). Sir i am usingFAR model more than one
order for which no statistical package is available inR, so for this i convert
my data into functional form and obtained thefunctional principle component and
from those FPCA i extract theircorresponding FPCscores. Know i use the VAR
model on those FPCscores forthe forecasting of each 24 hours through the VAR
model, but the VAR give me theforecasted value for all 23hours when i put
phat=23, but whenever i putphat=24 i.e want to predict each 24 hours its give
the results in the form ofNA. the code is given below
fdata<- function(mat){
nb = 27 # number of basis functions for the data
fbf = create.fourier.basis(rangeval=c(0,1), nbasis=nb) #basis for data
args=seq(0,1,length=24)
fdata1=Data2fd(args,y=t(mat),fbf) # functions generatedfrom discretized y
return(fdata1)
}
prediction.ffpe = function(fdata1){
n = ncol(fdata1$coef)
D = nrow(fdata1$coef)
#center the data
#mu = mean.fd(fdata1)
data = center.fd(fdata1)
#ffpe = fFPE(fdata1, Pmax=10)
#p.hat = ffpe[2] #order of the model
d.hat=23
p.hat=6
#fPCA
fpca = pca.fd(data,nharm=D, centerfns=TRUE)
scores = fpca$scores[,0:d.hat]
# to avoid warnings from vars predict function below
colnames(scores) <- as.character(seq(1:d.hat))
VAR.pre= predict(VAR(scores, p.hat), n.ahead=1,type="const")$fcst
}
kindly guide me that how can i solve out my problem or whaterror i doing. THANKS
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