Hi I am a newbie in R. I have data with dim of 20. How to use lm if i want to do regression with the whole design matrix? My y is the first column. the left are xs. Thanks a lot. -- View this message in context: http://r.789695.n4.nabble.com/how-to-do-linear-regression-when-dimension-is-high-tp3045167p3045167.html Sent from the R help mailing list archive at Nabble.com.
Douglas Bates
2010-Nov-16 17:20 UTC
[R] how to do linear regression when dimension is high
On Tue, Nov 16, 2010 at 10:30 AM, poko2000 <quan.poko2000 at gmail.com> wrote:> Hi I am a newbie in R. > I have data with dim of 20. > How to use lm if i want to do regression with the whole design matrix? My y > is the first column. > the left are xs. > Thanks a lot.Do you have the data stored in a matrix or in a data frame? If it is in a data frame and the first column is named "y" then you can use a call like lm(y ~ ., mydata) The '.' on the right hand side of the formula is expanded to a formula incorporating of the columns in the data frame except for the response. For example> summary(lm(Fertility ~ ., swiss))Call: lm(formula = Fertility ~ ., data = swiss) Residuals: Min 1Q Median 3Q Max -15.2743 -5.2617 0.5032 4.1198 15.3213 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 66.91518 10.70604 6.250 1.91e-07 Agriculture -0.17211 0.07030 -2.448 0.01873 Examination -0.25801 0.25388 -1.016 0.31546 Education -0.87094 0.18303 -4.758 2.43e-05 Catholic 0.10412 0.03526 2.953 0.00519 Infant.Mortality 1.07705 0.38172 2.822 0.00734 Residual standard error: 7.165 on 41 degrees of freedom Multiple R-squared: 0.7067, Adjusted R-squared: 0.671 F-statistic: 19.76 on 5 and 41 DF, p-value: 5.594e-10