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...@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]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.