Re: Multiple Regression

*To*: mathgroup at smc.vnet.net*Subject*: [mg50308] Re: Multiple Regression*From*: koopman at sfu.ca (Ray Koopman)*Date*: Thu, 26 Aug 2004 06:50:58 -0400 (EDT)*References*: <cghg7o$jgh$1@smc.vnet.net>*Sender*: owner-wri-mathgroup at wolfram.com

"Doug" <umdougmm at hotmail.com> wrote in message news:<cghg7o$jgh$1 at smc.vnet.net>... > [...] > I'm trying to come up with a model of the following sort: y = > (B0) + (B1)*(o01) + (B2)*(o02) + (B3)*(o03) + (B4)*(o04) + (B5)*(u) > + (B6)*(v) + (B7)*(w) + (B8)*(z) + (B9)*(y) + (B10)*(x) + epsilon > and I'm of course trying to minimize epsilon. Also, the other > important point is that o01 to o04 are binary and can be 1 only > exclusively (ie, if a data row has o01=1 then o02=..=o04=0, and the > same thing goes for the other o02 to o04) > > The variables which are causing me much headache are the o01..o04, > because if I include all the ~50 000 rows of data and run the Fit[] > function as follows: > Fit[Data,{1,o01,o02,o03,o04,u,v,w,z,y,x},{o01,o02,o03,o04,u,v,w,z,y,x}] > > the approximated B1=..=B4 are all equal and VERY large. [...] Your model is singular: o01 + o02 + o03 + o04 = 1. Drop the additive constant (1) or one of the o0i variables.