Return-Path: X-Original-To: apmail-commons-issues-archive@minotaur.apache.org Delivered-To: apmail-commons-issues-archive@minotaur.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 8152E10345 for ; Thu, 27 Feb 2014 14:41:40 +0000 (UTC) Received: (qmail 45425 invoked by uid 500); 27 Feb 2014 14:41:21 -0000 Delivered-To: apmail-commons-issues-archive@commons.apache.org Received: (qmail 45324 invoked by uid 500); 27 Feb 2014 14:41:20 -0000 Mailing-List: contact issues-help@commons.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: issues@commons.apache.org Delivered-To: mailing list issues@commons.apache.org Received: (qmail 45297 invoked by uid 99); 27 Feb 2014 14:41:20 -0000 Received: from arcas.apache.org (HELO arcas.apache.org) (140.211.11.28) by apache.org (qpsmtpd/0.29) with ESMTP; Thu, 27 Feb 2014 14:41:20 +0000 Date: Thu, 27 Feb 2014 14:41:20 +0000 (UTC) From: "Bruce A Johnson (JIRA)" To: issues@commons.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Commented] (MATH-1009) PolynomialFitter MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/MATH-1009?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13914580#comment-13914580 ] Bruce A Johnson commented on MATH-1009: --------------------------------------- Yes, as far as I can tell PolynomialCurveFitter extends AbstractCurveFitter which uses the non-linear LevenbergMarquardt method > PolynomialFitter > ---------------- > > Key: MATH-1009 > URL: https://issues.apache.org/jira/browse/MATH-1009 > Project: Commons Math > Issue Type: Improvement > Affects Versions: 3.2 > Environment: All > Reporter: Konstantin Berlin > Priority: Minor > Fix For: 3.3 > > > org.apache.commons.math3.fitting.PolynomialFitter > should be implemented using linear least-squares method like QR decomposition solver. > There are several reasons for this > 1) Nonlinear methods are much slower > 2) Linear methods (QR and SVD) are numerically more stable. > 3) By storing the QR decomposition it is possible to recompute the solution for different input data values. > See > http://mathworld.wolfram.com/LeastSquaresFittingPolynomial.html -- This message was sent by Atlassian JIRA (v6.1.5#6160)