search for: pop75

Here is an example, modified from the help page to use test="Cp": -------------------------------------------------------------------------------- > fit0 <- lm(sr ~ 1, data = LifeCycleSavings) > fit1 <- update(fit0, . ~ . + pop15) > fit2 <- update(fit1, . ~ . + pop75) > anova(fit0, fit1, fit2, test="Cp") Error in `[.data.frame`(table, , "Resid. Dev") : undefined columns selected > sessionInfo() R version 2.13.0 Patched (2011-04-28 r55678) Platform: i386-pc-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=English_United States.1252 [2]...

Hello to the whole group. I am a newbie to R, but I got my way through and think it is a lot easier to handle than other software packages (far less clicks necessary). However, I have a problem with respect to the summary of regression results. The summary function gives sth like: Residuals: Min 1Q Median 3Q Max -0.46743 -0.09772 0.01810 0.11175 0.42252

Hello: I am trying to understand the method 'hatvalues(...)', which returns something similar to the diagonals of the plain vanilla hat matrix [X(X'X)^(-1)X'], but not quite.  A Fortran programmer I am not, but tracing through the code it looks like perhaps some sort of correction based on the notion of 'leave-one-out' variance is being applied. Whatever the

Hello, I have spent a good deal of time searching for an answer to this but have come up empty-handed; I apologize if I missed something that is common knowledge. I am trying to figure out how to get an ANOVA table that shows the sum of squares. degrees of freedom, etc, for the full model versus the error (aka residuals). Here is an example of the kind of table I'd like to get:

...x Mean Sq.x F value.x Pr(>F).x Df.y Sum Sq.y > 1 ddpi NA NA NA NA NA 1 63.05403 > 2 dpi NA NA NA NA NA 1 12.40095 > 3 pop15 1 204.11757 204.11757 13.211166 0.000687868 1 204.11757 > 4 pop75 1 53.34271 53.34271 3.452517 0.069425385 1 53.34271 > 5 Residuals 47 726.16797 15.45038 NA NA 45 650.71300 > Mean Sq.y F value.y Pr(>F).y > 1 63.05403 4.3604959 0.0424711387 > 2 12.40095 0.8575863 0.3593550848 > 3 204.11757 14.1157322 0.00...