[R] time series transformation....

akshay kulkarni @k@h@y_e4 @end|ng |rom hotm@||@com
Mon Aug 14 20:55:45 CEST 2023


Dear ERic,
                 THanks a lot....!

THanking you,
Yours sincerely,
AKSHAY M KULKARNI
________________________________
From: Eric Berger <ericjberger using gmail.com>
Sent: Monday, August 14, 2023 11:04 PM
To: akshay kulkarni <akshay_e4 using hotmail.com>
Cc: R help Mailing list <r-help using r-project.org>
Subject: Re: [R] time series transformation....

Hi Akshay,
If you do
> help(package="forecast")

you will find that arfima is listed. Unfortunately, I don't see any
ARCH-type models there, but you should check out the help page
results.

Good luck,
Eric

On Mon, Aug 14, 2023 at 8:04 PM akshay kulkarni <akshay_e4 using hotmail.com> wrote:
>
> Dear Eric,
>                  THanks for the reply...will this also work with arfima() ? What if I want to fit a model like GARCH and friends?
>
> THanking you,
> Yours sincerely,
> AKSHAY M KULKARNI
> ________________________________
> From: Eric Berger <ericjberger using gmail.com>
> Sent: Sunday, August 13, 2023 10:34 AM
> To: akshay kulkarni <akshay_e4 using hotmail.com>
> Cc: R help Mailing list <r-help using r-project.org>
> Subject: Re: [R] time series transformation....
>
> Hi Akshay,
> The forecast package will do the BoxCox transform and automatically
> backtransform the forecasts.
> The package also handles xts objects.
> For example, modifying the example from the help page of
> forecast::forecast for Arima
>
> > dt <- as.Date("2023-01-01") + 1:length(WWWusage)
> > a <- xts(WWWusage, order.by=dt)
> > fit1 <- Arima(a, c(3,1,0))
> > fit2 <- Arima(a, lambda=0.5, c(3,1,0))  ## applies the Box-Cox transform with lambda=0.5
> > par(mfrow=c(1,2))
> > plot(forecast(fit1))
> > plot(forecast(fit2))
>
> HTH,
> Eric
>
> p.s. RJH is the author/maintainer of the forecast package
>
>
> On Sun, Aug 13, 2023 at 1:01 AM akshay kulkarni <akshay_e4 using hotmail.com> wrote:
> >
> > dear members,
> >                          I have a heteroscedastic time series which I want to transform to make it homoscedastic by a box cox transformation. I am using Otexts by RJ hyndman and George Athanopolous as my textbook. They discuss transformation and also say the fpp3 and the fable package automatically back transforms the point forecast. they also discuss the process which I find to be very cumbersome. Is there any R package which automatically back transforms the point forecast when I use xts objects ( RJH and GA use tsibble objects) with arfima/arima in the forecast package?
> >
> > THanking you,
> > Yours sincerely,
> > AKSHAY M KULKARNI
> >
> >         [[alternative HTML version deleted]]
> >
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