>
> Please note that your "df" and "M" are undoubtedly different
> objects by now:
>
> Right. Not my most coherent day.
thanks
W
> > M <- matrix(runif(5*20), nrow=20)
> > colnames(M) <- c('a', 'b', 'c', 'd', 'e')
> > l1 <- lm(e~., data=as.data.frame(M))
> > l1
>
> Call:
> lm(formula = e ~ .,
On Dec 2, 2011, at 11:20 PM, Worik R wrote:
Duh! Silly me! But my confusion persits: What is the regression
being
done? See below
Please note that your "df" and "M" are undoubtedly different
objects by now:
> M <- matrix(runif(5*20), nrow=20)
> colnames(M) <- c('a', 'b', 'c',
Duh! Silly me! But my confusion persits: What is the regression being
done? See below
On Sat, Dec 3, 2011 at 5:10 PM, R. Michael Weylandt <
michael.weyla...@gmail.com> wrote:
> In your code by supplying a vector M[,"e"] you are regressing "e"
> against all the variables provided in the da
In your code by supplying a vector M[,"e"] you are regressing "e"
against all the variables provided in the data argument, including "e"
itself -- this gives the very strange regression coefficients you
observe. R has no way to know that that's somehow related to the "e"
it sees in the data argumen
>
> Use `lm` the way it is designed to be used, with a data argument:
>
> > l2 <- lm(e~. , data=as.data.frame(M))
> > summary(l2)
>
> Call:
> lm(formula = e ~ ., data = as.data.frame(M))
>
>
And what is the regression being done in this case? How are the
independent variables used?
It looks like
On Dec 1, 2011, at 10:50 PM, Worik R wrote:
I really would like to be able to read about this in a document but I
cannot find my way around the documentation properly
Given the code...
M <- matrix(runif(5*20), nrow=20)
colnames(M) <- c('a', 'b', 'c', 'd', 'e')
ind <- c(1,2,3,4)
dep <- 5
I ca
I really would like to be able to read about this in a document but I
cannot find my way around the documentation properly
Given the code...
M <- matrix(runif(5*20), nrow=20)
colnames(M) <- c('a', 'b', 'c', 'd', 'e')
ind <- c(1,2,3,4)
dep <- 5
I can then do...
l2 <- lm(M[,dep]~M[,ind]) ## Clearl
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