Here's a little snippet on linear regression: http://www.mathworks.com/access/helpdesk/help/toolbox/stats/linear20.shtml#49537
The first equation is the common form (in matrix terms) of a linear model. It also defines residuals and other important points regarding multiple regression. The nice thing about linear models, is not only are they used for regression analysis, but they are the basis for ANOVA as well. So, I for one, would like to see a pure matrix based implementation for linear regression as it more likely reuseable for ANOVA. Also, we can add a facade to the matrix implementation for those whole just want to deal with double[] and double[][] structures. Much like we've done with the summary stats. Take note of the hat matrix. Some more advanced analysis like measuring the effect of an observation can be easily accomplished using the hat matrix. So, it might be worth while to incorporate caching of the hat matrix in any implementation. On Wed, 28 Jan 2004 12:46:32 -0500, "Inger, Matthew" wrote: > > by "model" are you referring to the "LinearRegressionResults" > class I had mentioned? I'm also no statistical guru. I can get > around where i need to, but i'm not sure what the "score" method > and "residuals" method is. I'm guessing you might be referring to > some of the linear regression statistics. A little clearer explantion > would help. I could submit what i have, and whomever can do the commit > might want to take these things into account, and possibly refactor > things a bit. I'm mainly concerened (for my project) with the > coefficient > matrix and predictions, but decided to go the extra step of computing > all the statistics that go along with it (figuring the community would > have use for them). Brent Worden http://www.brent.worden.org/ --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
