try something like the following:
x <- runif(1000, -3, 3)
y <- 2 + 3 * x + rnorm(1000)
f <- gl(10, 100)
lm.lis <- vector("list", 10)
for (i in 1:10) {
lm.lis[[i]] <- lm(y ~ x, subset = f == as.character(i))
}
sapply(lm.lis, coef)
sapply(lm.lis, fitted)
I hope it helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
Quoting Chip Barnaby <[EMAIL PROTECTED]>:
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 have experimented with various schemes, attempting to "pre-allocate"
a list etc. without success.
Also, I assume that lm() does not make a copy of input data? That is,
if I want "predict( LMX[ i])", I would have to retain a copy the
associated DXS subsets?
TIA,
Chip Barnaby
---------------------------------------------------------
Chip Barnaby [EMAIL PROTECTED]
Vice President of Research
Wrightsoft Corp. 781-862-8719 x118 voice
131 Hartwell Ave 781-861-2058 fax
Lexington, MA 02421 www.wrightsoft.com
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