search for: cbarnabi

Dear all, Is there a less cumbersome way to rename a column by name (as opposed to index) than -- names( X)[ names[ X] == "bob"]<-"sue" ? A semi-related question: how does one get the index of a column by name, something along the lines of col.index( X, "sue") ? Chip Barnaby --------------------------------------------------------- Chip Barnaby

Hello, I would like to create a subscriptable collection (presumably a list) of lm() models. I have a data frame DX containing 6 groups of data. The general idea is (NOT RUN) ... for (i in 1:6) { DXS = subset( DX, <whatever>); LMX[ i] = lm( <formula>, data = DXS); } Now access model results by subscript ... e.g. coefficients( LMX[ 2]). Or would it be [[ 2]]? I

Greetings, Q #1 ------ How does one combine data frames by row ... no cleverness a la merge(), just add rows. For example, given A with 20 rows and B with 30 rows, I want C = combine( A, B) having 50 rows. Columns having matching names should be filled from both (all) sources with suitable coercion, unmatched would get NA in rows whose source does not have that column. Q #2 ------ Given

Dear all -- I have a data frame containing data related to heat gain through windows. The general form is ... Key ProfA IAC <many other numeric columns> AAA 0 .7 AAA 10 .6 AAA 0 .66 AAA 20 .45 (more AAA rows) (then AAB rows) 'Key' identifies the physical configuration ... rows with a given Key contain data for same window under various

Dear all -- I want to compute weighted.mean() for grouped rows. Data frame extract is just below. For each Key, I want the mean of IAC weighted by Wt. DP0[1:20,] Key IAC Wt 2 C3-PD030020050.PD030020050.3.12.3.0 0.765 0.8590000 3 C3-PD030020050.PD030020050.3.12.3.0 0.764 0.8449651 4 C3-PD030020050.PD030020050.3.12.3.0

Dear R-ers, My aggregation saga continues. Using the following sequence, I can calculate any statistic for row groups and merge the result back to all associated rows ... > WM = by( D60, D60[ "KeyProfA"], FUN=function(x) weighted.mean( x$IAC, x$Wt)) > D60$IAC.WM = as.numeric( WM[ D60$KeyProfA]) > class( WM) [1] "by" Questions ... 1) Is this a reasonable way

Dear R-people ... I'm a new user. I can't get predict.lm() to produce predictions for new independent data. There are some messages in archived help about this problem, but I still don't see my error after reviewing those. I understand that the new independent data must have the same name(s) as used when the model was made. In the example below, predict.lm produces the