nonlinear regress on multiple data sets?
- To: mathgroup at smc.vnet.net
- Subject: [mg14528] nonlinear regress on multiple data sets?
- From: "Rajdeep S. Kalgutkar" <rajdeep at chem.nwu.edu>
- Date: Thu, 29 Oct 1998 04:33:25 -0500
- Sender: owner-wri-mathgroup at wolfram.com
Hello everybody! I have a question about nonlinear regression over multiple data sets. Is it possible using Mathematica? My problem is formulated like this: x*(y1*Eigenvec1+f(y1)*Eigenvec2) + (1-x)*(y2*Eigenvec1+f(y2)*Eigenvec2) = Obs. Data where: x can be from 0. - 1.; y1 and y2 are usually in a narrow range whose values depend on the data sets and eigenvectors under consideration; f(y1) and f(y2) are functions of y1 and y2 respectively; Eigenvec1 and Eigenvec2 are 2 eigenvectors (60 - 200 element vectors) by which I want to express my observed data (Obs. Data, same dimensions as eigenvectors). Now, I have multiple obs'd data. Usually I use Statistics`NonlinearRegress` to fit each individual data set. The values of y1 and y2 (and so f(y1) and f(y2)) should be the same for all the data sets and only x should change. Apart from minor variations the answers that I get for y1 and y2 are consistent for all data sets. However, it would be better if I could fit all the data sets simulataneously in a some sort of global fashion so as to obtain a global y1 and y2 with individual x's. Is this possible under Mathematica 3.0? Is so, how? I would really appreciate any help on this issue! rajdeep kalgutkar dept of chem nothwestern univ. rajdeep at chem.nwu.edu