It's a pity if BFAST is not developed and maintained... Hugo Roger Bivand <[email protected]> escreveu (sexta, 27/09/2024 à(s) 08:47):
> Could I suggest waiting until https://github.com/bfast2/bfast/issues/113 > which contains the same content has been attended to? Alternatively link to > the list archives in the github issue to ensure that any responses to one > channel do not get overlooked on the other channel (I've linked for now)? > Emailing directly or github pinging the package developers may also help if > this is urgent. Also consider reaching out to authors/maintainers of > packages using bfast https://cran.r-project.org/package=bfast, and look > (I'm sure you already have looked) among the many articles citing the > underlying work. The package description mentions a forthcoming paper on > BFAST Lite - this seems to be https://doi.org/10.3390/rs13163308. This > isn't my field, but I think that bfast isn't being developed actively, and > you may need to search broadly to try to resolve your issues, so looking at > how other users handle this may help. > > Hope this helps, > > Roger > > -- > Roger Bivand > Emeritus Professor > Norwegian School of Economics > Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway > [email protected] > > ________________________________________ > From: R-sig-Geo <[email protected]> on behalf of Nikolaos > Tziokas <[email protected]> > Sent: 27 September 2024 02:19 > To: r-sig-geo > Subject: [R-sig-Geo] Parameter tuning of the bfastlite function > > [You don't often get email from [email protected]. Learn why this > is important at https://aka.ms/LearnAboutSenderIdentification ] > > I am using the bfastlite() function from the BFAST package to run a > time-series analysis. From the author's paper (BFAST Lite: A Lightweight > Break Detection Method for Time Series Analysis) (table 2), I quote: > > "Needs parameter tuning to optimise performance, does not differentiate > between breaks in seasonality and trend" > > So far, I was fine-tuning the model manually, that is, I was changing the > parameters one by one, which is time-consuming. Does someone have a better > solution regarding the fine-tuning of the model? > > To see which parameters of the model achieve the best results, I was > checking the dates in the detected breakpoints (visual inspection). I am > not sure if that method (visual inspection) is appropriate. > > I apologize if this question sound a bit vague, so let me expand a little > bit. After running the bfastlite() using the default parameters (i.e., bp = > bfastlite(datats)), we get a result. Is there a way to measure (something > like rmse, or r-squared) how well the algorithm modeled the ts? What I > basically mean is that if there is an index equivalent to let's say rmse > when someone is running a linear regression. For example, what if the > parameter breaks with BIC instead of LWZ detects more accurate the > breakpoints (by visually inspecting the detected breakpoints)? Apart from > the visual inspection, shouldn't be some other way to measure the > performance of the model? > > Based on the above, is there a more efficient way to optimize the > parameters of the model (based on some metric)? What do I mean by > optimizing the parameters? I think with an example I can explain it better. > When someone is tuning a random forest model, he/she can perform a full > grid search to find the optimal parameters of the model (mtry, number of > trees, etc) by searching all the possible combinations and for each > combination he/she checks the rmse (or mse, r-squared). Is this what the > authors of the paper meant when they said "Needs parameter tuning to > optimise performance"? And if so, how did they do it? > > library(bfast) > > plot(simts) # stl object containing simulated NDVI time series > datats <- ts(rowSums(simts$time.series)) > > # sum of all the components (season,abrupt,remainder) > tsp(datats) <- tsp(simts$time.series) # assign correct time series > attributes > plot(datats) > > # Detect breaks. default parameters > bp = bfastlite(datats) > plot(bp) > > # optimized model ?????? > bp_opt <- bfastlite() > > R 4.4.1, bfast 1.6.1, Windows 11. > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > > _______________________________________________ > R-sig-Geo mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
