[R] time series transformation....

Eric Berger er|cjberger @end|ng |rom gm@||@com
Sun Aug 13 07:04:20 CEST 2023

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))


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,
>         [[alternative HTML version deleted]]
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