With 96k model fits it's going to be slow, so you might want to think
first about whether you need to do them all. Beyond that, I think this
is more in the R style, so might be quicker (I don't know how much the
loops are slowing you down), and even if not it should be easier to
adapt.
The other thing to think about is parallelising the code - the
parallel package should help.
FitModel <- function(K, data) {
z1 <- fourier(ts(data,frequency = 7), K=K["i"])
z2 <- fourier(ts(data,frequency=354), K=K["j"])
z3 <- fourier(ts(data,,frequency = 365),K=K["k"])
fit <- auto.arima(data,, xreg =cbind(z1,z2,z3), seasonal = FALSE)
fit$aicc
}
# smaller MaxOrders used so if you run it like this, it won't take 5 hours
MaxOrders <- expand.grid(i = 1:3, j=1=7, k=1:8)
AICc <- apply(MaxOrders, FitModel, data=demand)
Bob
AICc<- data.table(matrix(nrow = 96642, ncol = 4))for (i in 1:3) {
> > for (j in 1:177) {
> > for (k in 182) { #i,j and k values are choosen
> > with regad that K cannot exceed seasonality period/2
> > z1 <- fourier(ts(demand,frequency = 7), K=i)
> > z2 <- fourier(ts(demand,frequency=354), K=j)
> > z3 <- fourier(ts(demand,frequency = 365),K=k)
> > fit <- auto.arima(demand, xreg =cbind(z1,z2,z3),
> > seasonal = FALSE)
> > fit$aicc
> > AICc[,1]<-i
> > AICc[,2]<-j
> > AICc[,3]<-k
> > AICc[,4]<-fit$aicc
> > }
> >change
> > }
> > }
> > AICc
On Thu, 7 Feb 2019 at 13:44, salah maadawy <salahmaad...@gmail.com> wrote:
>
> Hi Micheal, Maybe there is a simple way but i wanted to get the lowest aicc
> ana i could not find a way to do so, that's why i created the table to
> store all possible outcomes and then i can easily get the minimum value and
> the values of (i,j and k) used for that minimum value. The first column in
> the table is AICc[,1] to store i and second column for j and so on. Maybe i
> am mistaken and this won't give me what i want, the code been running for 5
> hours now. So i am waiting
>
> On Wed, Feb 6, 2019 at 4:59 PM Michael Dewey <li...@dewey.myzen.co.uk>
> wrote:
>
> > This is not an answer to your speed problem but are your assignments to
> > AICc[,1] and so on doing what you hope they are doing?
> >
> > Michael
> >
> > On 06/02/2019 12:03, salah maadawy wrote:
> > > i am a beginner regarding R but i am trying to do a simple thing, but it
> > is
> > > taking too much time and i am asking if there is any way to achieve what
> > i
> > > need, i have a time series data set with 730 data points, i detected 7,
> > 354
> > > and 365 seasonality periods. i am trying to use Fourier terms for
> > > seasonality and for loop to get the K value for each while minimizing
> > AICc,
> > > my code is
> > >
> > > AICc<- data.table(matrix(nrow = 96642, ncol = 4))for (i in 1:3) {
> > > for (j in 1:177) {
> > > for (k in 182) { #i,j and k values are choosen
> > > with regad that K cannot exceed seasonality period/2
> > > z1 <- fourier(ts(demand,frequency = 7), K=i)
> > > z2 <- fourier(ts(demand,frequency=354), K=j)
> > > z3 <- fourier(ts(demand,frequency = 365),K=k)
> > > fit <- auto.arima(demand, xreg =cbind(z1,z2,z3),
> > > seasonal = FALSE)
> > > fit$aicc
> > > AICc[,1]<-i
> > > AICc[,2]<-j
> > > AICc[,3]<-k
> > > AICc[,4]<-fit$aicc
> > > }
> > >
> > > }
> > > }
> > > AICc
> > >
> > > i have created a data table to store AICc values from all possible i,j,k
> > > combinations so that i can find later the minimum AICc value. the problem
> > > now is that it is taking forever to do so not only to iterate all
> > > combinations but also due to the large K values.
> > >
> > > , is there any possible solution for this? thank you in advance
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > ______________________________________________
> > > R-help@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.
> > >
> >
> > --
> > Michael
> > http://www.dewey.myzen.co.uk/home.html
> >
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@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.
--
Bob O'Hara
Institutt for matematiske fag
NTNU
7491 Trondheim
Norway
Mobile: +47 915 54 416
Journal of Negative Results - EEB: www.jnr-eeb.org
______________________________________________
R-help@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.
