model2 <- lm( x~y ) predict(model2, data.frame(y=26)) model2 is however not the inverse of model... if you need that then you need to handle that some other way than using predict, such as an invertible monotonic spline (or in this case a little algebra).
On January 26, 2021 1:11:39 AM PST, Luigi Marongiu <marongiu.lu...@gmail.com> wrote: >Hello, >I have a series of x/y and a model. I can interpolate a new value of x >using this model, but I get funny results if I give the y and look for >the correspondent x: >``` >> x = 1:10 >> y = 2*x+15 >> model <- lm(y~x) >> predict(model, data.frame(x=7.5)) > 1 >30 >> predict(model, data.frame(y=26)) > 1 2 3 4 5 6 7 8 9 10 >17 19 21 23 25 27 29 31 33 35 >Warning message: >'newdata' had 1 row but variables found have 10 rows >> data.frame(x=7.5) > x >1 7.5 >> data.frame(y=26) > y >1 26 >``` >what is the correct syntax? >Thank you >Luigi > >______________________________________________ >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. -- Sent from my phone. Please excuse my brevity. ______________________________________________ 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.
