On Jun 25, 2010, at 7:09 AM, phani kishan wrote:
On Fri, Jun 25, 2010 at 1:54 PM, Paul Hiemstra
<p.hiems...@geo.uu.nl> wrote:
On 06/25/2010 10:02 AM, phani kishan wrote:
Hey,
I have a data frame x which consists of say 10 vectors. I
essentially want
to find out the best fit exponential smoothing for each of the
vectors.
The problem while I'm getting results when i say
lapply(x,ets)
I am getting an error when I say
myprint
function(x)
{
for(i in 1:length(x))
{
ets(x[i],model="AZZ",opt.crit=c("amse"))
Hi,
Please provide a reproducible example, as stated in the posting
guide. My
guess is that replacing x[i] by x[[i]] would solve the problem.
Double
brackets return a vector in stead of a data.frame that has just
column i.
Hey Paul,
As requested.
My example data frame
sdata:
SKU1 SKU2 SKU3 SKU4
1 583.8 574.6 1106.9
648.1
2 441.7 552.8 1021.3
353.6
3 454.2 555.7 998.3
306.4
4 569.7 507.6 811.1
360.7
5 512.3 620.0 1046.3
713.9
6 580.8 668.2 732.0
490.9
7 648.5 766.9 653.4
422.1
8 617.4 657.1 602.1
190.8
9 826.8 767.3 640.5
324.1
10 1163.0 657.6 429.6
181.1
11 643.5 788.9 569.1
331.9
12 846.9 568.6 425.1
224.6
13 580.7 582.9 434.2
226.9
now when I apply
lapply(sdata,ets)
I get a result as:
$SKU1
ETS(A,N,N)
Call:
ets(y = x, model = "AZZ")
Smoothing parameters:
alpha = 0.3845
Initial states:
l = 533.3698
sigma: 181.7615
AIC AICc BIC
172.6144 173.8144 173.7443
$SKU2
ETS(A,N,N)
Call:
ets(y = x, model = "AZZ")
Smoothing parameters:
alpha = 0.5026
Initial states:
l = 567.821
sigma: 86.7074
AIC AICc BIC
153.3704 154.5704 154.5003
$SKU3
ETS(A,A,N)
Call:
ets(y = x, model = "AZZ")
Smoothing parameters:
alpha = 1e-04
beta = 1e-04
Initial states:
l = 1189.2221
b = -64.3776
sigma: 85.4153
AIC AICc BIC
156.9800 161.9800 159.2398
$SKU4
ETS(A,A,N)
Call:
ets(y = x, model = "AZZ")
Smoothing parameters:
alpha = 1e-04
beta = 1e-04
Initial states:
l = 566.9001
b = -27.8818
sigma: 127.2654
AIC AICc BIC
167.3475 172.3475 169.6073
Now when I run the same using:
myfun<-function(x)
{
for(i in 1:length(x))
{
ets(x[i])
}
}
I got the error as mentioned before. Now on modifying it to
myfun<-function(x)
{
for(i in 1:length(x))
{
return(ets(x[[i]])
}
}
I only got the output as
ETS(A,N,N)
Call:
ets(y = x[[i]], model = "AZZ", opt.crit = c("amse"))
Smoothing parameters:
alpha = 0.3983
Initial states:
l = 516.188
sigma: 181.8688
AIC AICc BIC
172.6298 173.8298 173.7597
I think its considering whole dataframe as a series.
Doubtful. It is quietly calculating all of the requested models but
you did not do anything with them inside the loop (which is a
function). You could have assigned them to something permanent or
printed them (or both):
ets_x <- list()
for(i in 1:length(x))
{
print(ets(x[[i]]); ets_x <- c(ets_x, ets(x[[i]])
}
}
ets_x
As said my objective it to essentially come up with a best
exponential model
for each of the SKU's in the dataframe. However I want to be able to
extract
information like mse, mape etc later. So kindly suggest.
Thanks in advance,
Phani
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