Hi, I have been examining large data and need to do simple linear regression with the data which is grouped based on the values of a particular attribute. For instance, consider three columns : ID, x, y, and I need to regress x on y for each distinct value of ID. Specifically, for the set of data corresponding to each of the 4 values of ID (76,111,121,168) in the below data, I should invoke linear regression 4 times. The challenge is that, the length of the ID vector is around 20000 and therefore linear regression must be done automatically for each distinct value of ID.
ID x y 76 36476 15.8 76 36493 66.9 76 36579 65.6 111 35465 10.3 111 35756 4.8 121 38183 16 121 38184 15 121 38254 9.6 121 38255 7 168 37727 21.9 168 37739 29.7 168 37746 97.4 I was wondering whether there is an easy way to group data based on the values of ID in R so that linear regression can be done easily for each group determined by each value of ID. Or, is the only way to construct loops with 'for' or 'while' in which a matrix is generated for each distinct value of ID that stores corresponding values of x and y by screening the entire ID vector? Thanks in advance, Yasin [[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.