The answer to your question three is that the calculation of r-squared
in summary.lm does depend on whether or not an intercept is included in
the model. (Another part of the reason for you puzzlement is, I think,
that you are computing R-squared as SSR/SST, which is only valid when
when the
李俊杰 klijunjie at gmail.com writes:
Hi, Lynch,
Thank you for attention first.
I am also not a statistician and have just taken several statistics classes.
So it is natral for us to ask some question seeming naive to statisticans.
I am sorry that I cannot agree with your point that we
Hi,Oksanen,
Thanks for your reply.
I agree with you at the point that if we misjudge none-zero intercept to be
zero, there will be loss still or even great loss as you and Venables
emphasized in your practical research work. If there won't be any loss when
we misjudge
zero intercept to be
On 5/21/07, Alberto Monteiro [EMAIL PROTECTED] wrote:
Paul Lynch wrote:
I don't think it makes sense to compare models with
and without an intercept term. (Also, I don't know what the point of
using a model without an intercept term would be, but that is
probably just my ignorance.)
Junjie,
First, a disclaimer: I am not a statistician, and have only taken
one statistics class, but I just took it this Spring, so the concepts
of linear regression are relatively fresh in my head and hopefully I
will not be too inaccurate.
According to my statistics textbook, when
Paul Lynch wrote:
I don't think it makes sense to compare models with
and without an intercept term. (Also, I don't know what the point of
using a model without an intercept term would be, but that is
probably just my ignorance.)
Suppose that you are 100% sure that the intercept term is
Hi, Lynch,
Thank you for attention first.
I am also not a statistician and have just taken several statistics classes.
So it is natral for us to ask some question seeming naive to statisticans.
I am sorry that I cannot agree with your point that we must always include
intercept in our model.
, 2007 2:54 AM
To: Paul Lynch
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] R2 always increases as variables are added?
I know that -1 indicates to remove the intercept term. But my question
is why intercept term CAN NOT be treated as a variable term as we place a
column consited of 1
I know that -1 indicates to remove the intercept term. But my question is
why intercept term CAN NOT be treated as a variable term as we place a
column consited of 1 in the predictor matrix.
If I stick to make a comparison between a model with intercept and one
without intercept on adjusted r2
Hi, everybody,
3 questions about R-square:
-(1)--- Does R2 always increase as variables are added?
-(2)--- Does R2 always greater than 1?
-(3)--- How is R2 in summary(lm(y~x-1))$r.squared
calculated? It is different from (r.square=sum((y.hat-mean
On 17/05/2007 7:02 AM, ??? wrote:
Hi, everybody,
3 questions about R-square:
-(1)--- Does R2 always increase as variables are added?
-(2)--- Does R2 always greater than 1?
-(3)--- How is R2 in summary(lm(y~x-1))$r.squared
calculated? It
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