R help - Oct 2020 - Help in R code

Good morning,??Please help me to code this code in R.
I working in the multivariate time series data, know my objective is that to one
year forecast of the hourly time series data, using first five as a training set
and the remaining one year as validation. For this??I transform the the data
into functional data through Fourier basis functional, apply functional
principle components as dimensional reduction explaining a specific amount of
variation? ?, using the corresponding? functional principle components scores. I
use the VAR model on those FPCscores for forecasting one day ahead forecast,
know my problem is that i choose four Fpc scores which give only four value in a
single day, I want the forecast for 24 hours not only 4, and then i want to
transform it back to the original functional data. for the understanding i am
sharing my code (1) transform of the multivariate time series data in functional
data(2) the functional principle components and the corresponding scores(3) I
use functional final prediction error for the selection of the parameters on the
VAR model(4) Using VAR for the analysis and forecasting .(1)?nb = 23 # 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 generated from discretized
y(2)?ffpe = fFPE(fdata1, Pmax=10)? d.hat = ffpe[1] #order of the model? p.hat =
ffpe[2] #lag of the model
(3) n = ncol(fdata1$coef)? D = nrow(fdata1$coef)? #center the data? mu =
mean.fd(fdata1)? data = center.fd(fdata1)? #fPCA? fpca = pca.fd(data,nharm=D)?
scores = fpca$scores[,1:d.hat](4)?# to avoid warnings from vars predict function
below? ? ? colnames(scores) <- as.character(seq(1:d.hat))? ? ? VAR.pre=
predict(VAR(scores, p.hat), n.ahead=1, type="const")$fcst
after this I need help first how to transform this into original Functional data
and to obtain the for for each 24 hours (mean one day forecast) and to how to
generalize the result for one year.


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I think you first should read and understand this:
https://stackoverflow.com/help/minimal-reproducible-example
and
https://stackoverflow.com/help/how-to-ask

On Sun, Oct 18, 2020, 11:57 Faheem Jan via R-help <r-help at
r-project.org>
wrote:
> Good morning,  Please help me to code this code in R.
> I working in the multivariate time series data, know my objective is that
> to one year forecast of the hourly time series data, using first five as a
> training set and the remaining one year as validation. For this  I
> transform the the data into functional data through Fourier basis
> functional, apply functional principle components as dimensional reduction
> explaining a specific amount of variation   , using the corresponding
> functional principle components scores. I use the VAR model on those
> FPCscores for forecasting one day ahead forecast, know my problem is that i
> choose four Fpc scores which give only four value in a single day, I want
> the forecast for 24 hours not only 4, and then i want to transform it back
> to the original functional data. for the understanding i am sharing my code
> (1) transform of the multivariate time series data in functional data(2)
> the functional principle components and the corresponding scores(3) I use
> functional final prediction error for the selection of the parameters on
> the VAR model(4) Using VAR for the analysis and forecasting .(1) nb = 23 #
> 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
> generated from discretized y(2) ffpe = fFPE(fdata1, Pmax=10)  d.hat >
ffpe[1] #order of the model  p.hat = ffpe[2] #lag of the model
> (3) n = ncol(fdata1$coef)  D = nrow(fdata1$coef)  #center the data  mu >
mean.fd(fdata1)  data = center.fd(fdata1)  #fPCA  fpca > pca.fd(data,nharm=D)
scores = fpca$scores[,1:d.hat](4) # to avoid warnings
> from vars predict function below      colnames(scores) <-
> as.character(seq(1:d.hat))      VAR.pre= predict(VAR(scores, p.hat),
> n.ahead=1, type="const")$fcst
> after this I need help first how to transform this into original
> Functional data and to obtain the for for each 24 hours (mean one day
> forecast) and to how to generalize the result for one year.
>
>
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>
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