Hello, Apologies if this question has already arised, hope you can help me to the find the solution to this or point the place to look at. I have a multidimensional piece-wise regression linear problem, i.e. to find not only the regression coefficients for each "interval" but also the beginning and ends of the intervals. To simplify it to the one dimensional case and two intervals, the problem is to find A_0, A_1, ... A_p and "C" from the given sample, assuming the curve is like this: A_0*f_0(x)+A_1*f_1(x)+ ... + A_p*f_p(x) with x < C A_0'*f_0(x)+A_1'*f_1(x)+ ... + A_p'*f_p(x) with x >= C Functions f_1, f_2, ... f_p are known. Is there anything in R for that? I have tried to use nonlinear (nls package) regression, "forcing" with the "nls" function the shape of the surface, but it does not work. By the way, the cofficients A_i have to be positive, but I suppose this is another question. Thanks Casiano casiano at ull.es
piece wise functions
2 messages · Casiano Rodriguez Leon, Thomas W Blackwell
Casiano - A practical approach would be to use gam() and its friends in package mgcv. This implements Generalized Additive Models (Hastie & Tibshirani, 1990). The fit will be smoother than you would get with an explicit piece-wise linear regression, but it's already implemented. If you really care about estimating the boundaries between distinct regions of the fit, that's a research question, in my humble opinion, and you are cast onto the stormy sea of statistical literature for that. That's a difficult problem. Start with gam() and eyeball the boundaries ? Others will have better ideas. Maybe packages "GRASS", "grasper" or "geoR" have something to offer ? - tom blackwell - u michigan medical school - ann arbor -
On Mon, 21 Apr 2003, Casiano Rodriguez Leon wrote:
Hello, I have a multidimensional piece-wise regression linear problem, i.e. to find not only the regression coefficients for each "interval" but also the beginning and ends of the intervals. To simplify it to the one dimensional case and two intervals, the problem is to find A_0, A_1, ... A_p and "C" from the given sample, assuming the curve is like this: A_0*f_0(x)+A_1*f_1(x)+ ... + A_p*f_p(x) with x < C A_0'*f_0(x)+A_1'*f_1(x)+ ... + A_p'*f_p(x) with x >= C Functions f_1, f_2, ... f_p are known. Is there anything in R for that? I have tried to use nonlinear (nls package) regression, "forcing" with the "nls" function the shape of the surface, but it does not work. By the way, the cofficients A_i have to be positive, but I suppose this is another question. Thanks Casiano casiano at ull.es