On Fri, 18 Nov 2005, Juni Joshi wrote:
I need to fit a number of models with different number of predictors
in each model. Say for example, I have three predictors: x1, x2, x3
and I want to fit three models:
lm(y~x1+x2)
lm(y~x2+x3)
lm(y~x1+x2+x3)
Instead of typing
try :
my_formula = as.formula(paste(y~,xxx))
lm(my_formula)
note that you can play with substr in paste to change your formula
paste(y~,substr(xxx,1,5))
[1] y~ x1+x2
paste(y~,substr(xxx,4,8))
[1] y~ x2+x3
furthermore, with 10 predictors x1 x2 ...x10 for instence, you can
create 2 array of
Juni Joshi wrote:
I need to fit a number of models with different number of predictors
in each model. Say for example, I have three predictors: x1, x2, x3
and I want to fit three models:
lm(y~x1+x2)
lm(y~x2+x3)
lm(y~x1+x2+x3)
Stepwise variable selection has so many
I need to fit a number of models with different number of predictors
in each model. Say for example, I have three predictors: x1, x2, x3
and I want to fit three models:
lm(y~x1+x2)
lm(y~x2+x3)
lm(y~x1+x2+x3)
Instead of typing all models, what I want is to create a
Try this:
x - data.frame(x1 = x1, x2 = x2, x3 = x3)
lm(y ~., x[,1:2])
lm(y ~., x[,2:3])
lm(y ~., x[,1:3])
On 11/18/05, Juni Joshi [EMAIL PROTECTED] wrote:
I need to fit a number of models with different number of predictors
in each model. Say for example, I have three predictors:
