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 <[email protected]> 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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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
