# [R] very slow code execution

Michael Dewey ||@t@ @end|ng |rom dewey@myzen@co@uk
Wed Feb 6 14:59:53 CET 2019

```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]]
>
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