On Oct 31, 2009, at 7:29 AM, tdm wrote:
OK, I think I've figured it out, the predict of lrm didn't seem to
pass it
through the logistic function. If I do this then the value is
similar to
that of lm. Is this by design?
Yes, at least for certain meanings of "this". When working with
p
tdm wrote:
>> OK, I think I've figured it out, the predict of lrm didn't seem to pass
>> it through the logistic
>> function. If I do this then the value is similar to that of lm. Is this
>> by design? Why would it
>> be so?
Please take some time to read the help files on these functions so th
OK, I think I've figured it out, the predict of lrm didn't seem to pass it
through the logistic function. If I do this then the value is similar to
that of lm. Is this by design? Why would it be so?
1 / (1 + Exp(-1 * 3.38)) = 0.967
tdm wrote:
>
>
> Anyway, do you know why the lrm predict g
f disappointing, I think the answer to your question is
> "no". You will need to seek out the algorithms from the published
> information on them individually.
>
> W.
>
> From: r-help-boun...@r-project.org [r-help-boun...@r-project.
Hi Phil,
>> So far for logistic regression I've tried glm(MASS) and lrm (Design) and
>> found there is a big
>> difference.
Be sure that you mean what you say, that you are saying what you mean, and
that you know what you mean when making such statements, especially on this
list. glm is not in
rg] On Behalf Of
tdm [ph...@philbrierley.com]
Sent: 31 October 2009 16:53
To: r-help@r-project.org
Subject: [R] Logistic and Linear Regression Libraries
Hi all,
I'm trying to discover the options available to me for logistic and linear
regression. I'm doing some tests on a dataset and want t
Hi all,
I'm trying to discover the options available to me for logistic and linear
regression. I'm doing some tests on a dataset and want to see how different
flavours of the algorithms cope.
So far for logistic regression I've tried glm(MASS) and lrm (Design) and
found there is a big differenc
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