Caveat: Did not look at any of your links. However, the usual answer for this sort of question is ?predict.gam (in general, predict.whatevermethod) Have you consulted the man page? If this is not what you want, you may need to explain more carefully.
Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Aug 11, 2020 at 5:21 AM Dileepkumar R <dileepkunj...@gmail.com> wrote: > Dear All, > > I am trying to estimate the non -linear trend value from smooth spline > trend fit (using the generalized additive model (GAM)). > > I want to estimate the trend value from a temperature dataset (spatial > averaged annual meantime from 1906 to 2005) as given in the Box 2.2, Table > 1 in the attached Google doc pdf. (That pages are from IPCC Assessment > Report 5 chapter 2 > < > https://www.ipcc.ch/site/assets/uploads/2017/09/WG1AR5_Chapter02_FINAL.pdf > >, > page number 21-22 ) > > I do not understand how they estimate the single value trend with 95% > confidence interval from a time-series data as given in the Box 2.2, Figure > 1. Is there any easy way to extract the trend value using mgcv library of > R.? > > Google Doc Link: > > https://drive.google.com/file/d/1z3XLW-154dsZE6GrvQ4rH_fev9lqdsho/view?usp=sharing > > Thank you all in advance > > Dileepkumar R > > [[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. > [[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.
