for loop and linear models

Hi:

(a) What Brian said...

(b) Here's one way to generate a list of model objects from which you
can extract the pieces you may want.

# Generate a fairly minimal, reproducible data set
set.seed(345)   # makes results below reproducible
dd <- data.frame(X = rnorm(100), Y = rnorm(100),
                  gp = factor(rep(LETTERS[1:5], each = 20)))

# Basically, split the data frame by gp into a list of sub-data frames
# and fit lm() to each piece. We use the plyr package for this:
library(plyr)
mlist <- dlply(dd, .(gp), function(d) lm(Y ~ X, data = d))

# mlist is a list of lm objects, from which you can extract salient
# pieces using the l*ply functions from plyr. For example,

# return the coefficients from each model fit:

ldply(mlist, coef)

gp (Intercept)            X
1  A -0.05670893 -0.008741077
2  B -0.41071309 -0.134832968
3  C -0.02007992  0.379762195
4  D  0.04168990  0.213085495
5  E  0.19094314  0.010481033

# R^2:

ldply(mlist, function(m) summary(m)$r.squared)

gp           V1
1  A 9.287934e-05
2  B 1.684219e-02
3  C 1.200286e-01
4  D 4.235989e-02
5  E 7.294735e-05

# Table of coefficients, SEs and significance tests
# (outputs a list)
llply(mlist, function(m) summary(m)$coefficients)

# Data frame of predicted values and residuals (multiple outputs):
ldply(mlist, function(m) data.frame(pred = fitted(m), res = resid(m)))

HTH,
Dennis

Hi,

I have two datasets, x and y. Simplified x and y denote:

?X

Y

?A B C A B C ?. . . . . . ?. . . . . . ?. . . . . .
I want to implement all possible models such as lm(X$A~Y$A), lm(X$B~Y$B),
lm(X$C~Y$C)... I have tried the following:

fun<- function(x,y){
? ? ? ? ? ?for(i in 1:length(colnames(x))){
? ? ? ? ? ? ?for(j in 1:length(colnames(y))){
? ? ? ? ? ? ? if(colnames(x)[i]==colnames(y)[j]){
? ? ? ? ? ? ? models=list(lm(ts(x[i])~ts(y[j])))
? ? ? ? ? ? ? }
? ? ? ? ? ? ? else{}
? ? ? ? ? ?}
? ? ? ? ?}
? ? ? ? ? return(models)
}

The problem is that this returns only one of the three models, namely the
last one. What am I doing wrong? Thank you very much in advance.

Regards

? ? ? ?[[alternative HTML version deleted]]

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