On Sun, 18 Feb 2007 07:46:56 +0000 (GMT) Prof Brian Ripley <[EMAIL PROTECTED]> wrote:
> On Sat, 17 Feb 2007, Ranjan Maitra wrote: > > > Dear list, > > > > I have a 4-dimensional array Y of dimension 330 x 67 x 35 x 51. I have a > > design matrix X of dimension 330 x 4. I want to fit a linear regression > > of each > > > > lm( Y[, i, j, k] ~ X). for each i, j, k. > > > > Can I do it in one shot without a loop? > > Yes. > > YY <- YY > dim(YY) <- c(330, 67*35*51) > fit <- lm(YY ~ X) > > > Actually, I am also interested in getting the p-values of some of the > > coefficients -- lets say the coefficient corresponding to the second > > column of the design matrix. Can the same be done using array-based > > operations? > > Use lapply(summary(fit), function(x) coef(x)[3,4]) (since there is a > intercept, you want the third coefficient). In this context, can one also get the variance-covariance matrix of the coefficients? Thank you, and best wishes! Ranjan > Note that this will give a vector, so set its dimension to c(67,35,51) to > relate to the original array. > > I have not BTW looked into the memory requirements here, and you might > want to do this on slices of the array for that reason. > > -- > Brian D. Ripley, [EMAIL PROTECTED] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > ______________________________________________ [email protected] 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.
