You can find out the model matrix like this where we use the builtin data frame CO2 to illustrate:
fo <- uptake ~ Treatment * Type mod <- lm(fo, CO2); mod mm <- model.matrix(fo, CO2) View(mm) On Sat, Feb 13, 2010 at 5:03 PM, Something Something <mailinglist...@gmail.com> wrote: > I tried.. > > mod = lm(Y ~ X1*X2*X3, na.action = na.exclude) > formula(mod) > > This produced.... > Y ~ X1 * X2 * X3 > > > When I typed just mod I got: > > Call: > lm(formula = Y ~ X1 * X2 * X3, na.action = na.exclude) > > Coefficients: > (Intercept) X11 X21 X31 X11:X21 X11:X31 > X21:X31 X11:X21:X31 > 177.9245 0.2005 2.4482 3.1216 0.8127 -26.6166 > -3.0398 29.6049 > > > I am trying to figure out how R computed all these coefficients. > > > > > > On Sat, Feb 13, 2010 at 1:30 PM, Bert Gunter <gunter.ber...@gene.com> wrote: > >> ?formula >> >> >> Bert Gunter >> Genentech Nonclinical Statistics >> >> -----Original Message----- >> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] >> On >> Behalf Of Something Something >> Sent: Saturday, February 13, 2010 1:24 PM >> To: Daniel Nordlund >> Cc: r-help@r-project.org >> Subject: Re: [R] lm function in R >> >> Thanks Dan. Yes that was very helpful. I didn't see the change from '*' >> to >> '+'. >> >> Seems like when I put * it means - interaction & when I put + it's not an >> interaction. >> >> Is it correct to assume then that... >> >> When I put + R evaluates the following equation: >> Y-Hat = b0 + b1X1 + b2X2 + . . . bkXk + 7 7 7 + bkXk >> >> >> But when I put * R evaluates the following equation; >> Y-Hat = b0 + b1X1 + b2x2 + ... + bkXk + b12 X12+ b13 X13 +........ + c >> >> Is this correct? If it is then can someone point me to any sources that >> will explain how the coefficients (such as b0... bk, b12.. , b123..) are >> calculated. I guess, one source is the R source code :) but is there any >> other documentation anywhere? >> >> Please let me know. Thanks. >> >> >> >> On Fri, Feb 12, 2010 at 5:54 PM, Daniel Nordlund >> <djnordl...@verizon.net>wrote: >> >> > > -----Original Message----- >> > > From: r-help-boun...@r-project.org [mailto: >> r-help-boun...@r-project.org] >> > > On Behalf Of Something Something >> > > Sent: Friday, February 12, 2010 5:28 PM >> > > To: Phil Spector; r-help@r-project.org >> > > Subject: Re: [R] lm function in R >> > > >> > > Thanks for the replies everyone. Greatly appreciate it. Some >> progress, >> > > but >> > > now I am getting the following values when I don't use "as.factor" >> > > >> > > 13.14167 25.11667 28.34167 49.14167 40.39167 66.86667 >> > > >> > > Is that what you guys get? >> > >> > >> > If you look at Phil's response below, no, that is not what he got. The >> > difference is that you are specifying an interaction, whereas Phil did >> not >> > (because the equation you initially specified did not include an >> > interaction. Use Y ~ X1 + X2 instead of Y ~ X1*X2 for your formula. >> > >> > > >> > > >> > > On Fri, Feb 12, 2010 at 5:00 PM, Phil Spector >> > > <spec...@stat.berkeley.edu>wrote: >> > > >> > > > By converting the two variables to factors, you are fitting >> > > > an entirely different model. Leave out the as.factor stuff >> > > > and it will work exactly as you want it to. >> > > > >> > > > dat >> > > >> >> > > > V1 V2 V3 V4 >> > > > 1 s1 14 4 1 >> > > > 2 s2 23 4 2 >> > > > 3 s3 30 7 2 >> > > > 4 s4 50 7 4 >> > > > 5 s5 39 10 3 >> > > > 6 s6 67 10 6 >> > > > >> > > >> names(dat) = c('id','y','x1','x2') >> > > >> z = lm(y~x1+x2,dat) >> > > >> predict(z) >> > > >> >> > > > 1 2 3 4 5 6 15.16667 >> 24.66667 >> > > > 27.66667 46.66667 40.16667 68.66667 >> > > > >> > > > >> > > > - Phil Spector >> > > > Statistical Computing >> Facility >> > > > Department of Statistics >> > > > UC Berkeley >> > > > spec...@stat.berkeley.edu >> > > > >> > > > >> > > > >> > > > On Fri, 12 Feb 2010, Something Something wrote: >> > > > >> > > > Hello, >> > > >> >> > > >> I am trying to learn how to perform Multiple Regression Analysis in >> R. >> > > I >> > > >> decided to take a simple example given in this PDF: >> > > >> http://www.utdallas.edu/~herve/abdi-prc-pretty.pdf >> > > >> >> > > >> I created a small CSV called, students.csv that contains the >> following >> > > >> data: >> > > >> >> > > >> s1 14 4 1 >> > > >> s2 23 4 2 >> > > >> s3 30 7 2 >> > > >> s4 50 7 4 >> > > >> s5 39 10 3 >> > > >> s6 67 10 6 >> > > >> >> > > >> Col headers: Student id, Memory span(Y), age(X1), speech rate(X2) >> > > >> >> > > >> Now the expected results are: >> > > >> >> > > >> yHat[0]:15.166666666666668 >> > > >> yHat[1]:24.666666666666668 >> > > >> yHat[2]:27.666666666666664 >> > > >> yHat[3]:46.666666666666664 >> > > >> yHat[4]:40.166666666666664 >> > > >> yHat[5]:68.66666666666667 >> > > >> >> > > >> This is based on the following equation (given in the PDF): Y = >> 1.67 >> > + >> > > X1 >> > > >> + >> > > >> 9.50 X2 >> > > >> >> > > >> I ran the following commands in R: >> > > >> >> > > >> data = read.table("students.csv", head=F, as.is=T, na.string=".", >> > > >> row.nam=NULL) >> > > >> X1 = as.factor(data[[3]]) >> > > >> X2 = as.factor(data[[4]]) >> > > >> Y = data[[2]] >> > > >> mod = lm(Y ~ X1*X2, na.action = na.exclude) >> > > >> Y.hat = fitted(mod) >> > > >> Y.hat >> > > >> >> > > >> This gives me the following output: >> > > >> >> > > >> Y.hat >> > > >>> >> > > >> 1 2 3 4 5 6 >> > > >> 14 23 30 50 39 67 >> > > >> >> > > >> Obviously I am doing something wrong. Please help. Thanks. >> > > >> >> > >> > Hope this is helpful, >> > >> > Dan >> > >> > Daniel Nordlund >> > Bothell, WA USA >> > >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> > >> >> [[alternative HTML version deleted]] >> >> >> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
