I tried using prcomp(): library(compositions) library(rgl) x <- rnorm(100) y <- rnorm(100) z <- rnorm(100) mat<-cbind(x,y,z) plot3D(mat,col=3,bbox=F) pr<-prcomp(mat) planes3d(pr$rotation[3,1]*sign(pr$rotation[3,1]),pr$rotation[3,2]*sign(pr$rotation[3,2]),pr$rotation[3,3]*sign(pr$rotation[3,3]),alpha=0.5,col=3,bbox=F) decorate3d()
It seems fine; any advice is welcome best paolo ________________________________________ Da: R-sig-ecology <r-sig-ecology-boun...@r-project.org> per conto di Paolo Piras <paolo.pi...@uniroma3.it> Inviato: martedì 19 gennaio 2016 14.46 A: r-sig-ecology@r-project.org Oggetto: [R-sig-eco] 3d fitting plane Hi folks, I look for a fast way to estimate a 3d fitting plane to my 3d data. I do not want z~y+x as this is a regression model. I just want the equation of the best plane that fits the data in 3d. Maybe using princomp() and Total least squares? Looking around I found some solutions but nothing definitive. Thanks in advance for any suggestion. best paolo _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
