Hey,
Thanks for the tip Stephan. But you could tell me how to pass the series to
the function calling ets?
Initially I planned to do it this way:

wrapper<-function(x)
{
alpha<-x[1]
beta<-x[2]
ph<-x[3]
series<-x[4]
foofit<-ets(series,model="AZZ",alpha=alpha,beta=beta,phi=phi,additive.only=T,opt.crit=c("mse"))
accuracy(foofit)[5]              ##for MAPE
}

I then planned to use the optim using
optim(c(alpha,beta,phi,series),wrapper)

What I hoped to do is also select MAPE as a criteria for selection of my
alpha and beta.
However I shouldn't pass my series in this form right? As it would be
"optimized" too in the process? Could you suggest a way around this.
And I did find a way around could this allow me to set MAPE as a criteria?

Phani



On Tue, Jun 29, 2010 at 12:47 AM, Stephan Kolassa <Stephan.Kolassa@gmx.de>wrote:

> Hi Phani,
>
> to get the best Holt's model, I would simply wrap a suitable function
> calling ets() within optim() and optimize for alpha and beta - the values
> given by ets() without constraints would probably be good starting values,
> but you had better start the optimization with a variety of starting values
> to make sure you don't end up in a local minimum.
>
> I know of no comparison just between Holt and Brown - but you could use the
> above methods and the M3 Competition dataset (in Mcomp) to look how the two
> methods compare on a (more or less) benchmark dataset.
>
> HTH
> Stephan
>
>
> phani kishan schrieb:
>
>  Hey,
>> I am using the ets() function in the forecast package to find out the best
>> fit parameters for my time-series. I have about 50 sets of time series
>> data.
>>
>> I'm currently using the function as follows:
>>
>> ets(x,model="AZZ",opt.crit="mse")
>>
>>
>> As to my observation about 5-10 of them have been identified by ets to
>> have
>> a trend and an alpha, beta values have been thrown up - which have been
>> same
>> in all these cases. When I read up online it came up as a Brown's double
>> exponential smoothing as opposed to Holt's exponential smoothing (where
>> alpha and beta differ). I am guessing this is happening as AIC/AICc/BIC
>> select a model based on accuracy as well as a weight on number of
>> parameters
>> (1 in case of brown's, 2 in case of holt's). Now if I want to see results
>> of
>> the best parameters from the Holt's method, how should I go about it?
>>
>> And is there any study comparing the accuracy of brown's double
>> exponential
>> model versus holt's exponential model?
>>
>> Thanks in advance,
>> Phani
>>
>>
>


-- 
A. Phani Kishan
3rd Year B.Tech
Dept. of Computer Science & Engineering
IIT MADRAS
Ph: +919962363545

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