very slow code execution

   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

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 <lists at 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

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