[From nobody Mon Jan 29 21:32:48 2007 Message-ID: <45BE5078.3070302@umich.edu> Date: Mon, 29 Jan 2007 14:52:24 -0500 From: Jonathon Kopecky <jkopecky@umich.edu> User-Agent: Thunderbird 1.5.0.9 (Windows/20061207) MIME-Version: 1.0 To: r-help@lists.R-project.org Subject: Need to fit a regression line using orthogonal residuals Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit I'm trying to fit a simple linear regression of just Y ~ X, but both X and Y are noisy. Thus instead of fitting a standard linear model minimizing vertical residuals, I would like to minimize orthogonal/perpendicular residuals. I have tried searching the R-packages, but have not found anything that seems suitable. I'm not sure what these types of residuals are typically called (they seem to have many different names), so that may be my trouble. I do not want to use Principal Components Analysis (as was answered to a previous questioner a few years ago), I just want to minimize the combined noise of my two variables. Is there a way for me to do this in R? Jonathon Kopecky University of Michigan ]