I posted before recently about fitting 3D data x, y, z where all have error attached. I want to predict z from x and y; something like z = b0 + b1*x + b2*y But multiple regression is not suitable because all of x, y, and z have errors.
I have plotted a 3D scatterplot of some data using rgl. I see that the data form a cigar-shaped cloud. I think multiple regression is only suitable when the points fall on a plane (forgetting about the error in x and y). I now know the right way how to find the best fitting plane to x,y,z data using princomp. But a new problem is how to get the best fitting *line*. I actually know how to do that too using princomp. But there is a mathematical problem: there's no way to specify a line in 3D space in the form z=f(x,y) or in other words with an intercept and slopes. Instead, one way to deal with the problem is to use a parametric version of the line: you use an arbitrary starting point x0, y0, z0 and the direction vector of your line (I know how to get the direction vector). BUT how do I get the intercept??? At this point my lines just go through the origin. Do I just use $center from the princomp output modified in some way? Thanks for any help! Cheers Bill ______________________________________________ R-help@r-project.org mailing list 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.
