R help - Oct 2020 - Help in R code

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


	[[alternative HTML version deleted]]

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

?s 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
> 
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>