Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Posting-Version: version B 2.10.1 6/24/83; site brl-tgr.ARPA Path: utzoo!watmath!clyde!burl!ulysses!unc!mcnc!decvax!genrad!wjh12!harvard!seismo!brl-tgr!gwyn From: gwyn@brl-tgr.ARPA (Doug Gwyn) Newsgroups: net.math Subject: Re: curve fitting (maybe) Message-ID: <4735@brl-tgr.ARPA> Date: Wed, 19-Sep-84 15:28:50 EDT Article-I.D.: brl-tgr.4735 Posted: Wed Sep 19 15:28:50 1984 Date-Received: Tue, 25-Sep-84 20:25:37 EDT References: <1197@cwruecmp.UUCP> Organization: Ballistics Research Lab Lines: 18 Judging by your diagram, you appear to want to take the existing data as samples of some vector field and then interpolate to find the field value at a given point. Without some conditions on the vector field there is of course no single solution to this problem. The diagram also shows multiple field values at a point. This implies "least squares" style fitting would be appropriate. To make this work I think there would have to be some implied order to the points. As a rough approximation, how about making the vector at the test point the weighted average of all known vectors, with the weights such that the nearest point (using Euclidean metric) scales the "range" of the weight and the total weights sum up to 1. E.g. except right at a data point, a Gaussian function of distance from the test point could be used.