Stephen Dubin wrote:
>I often see (and use) the term "metric" as a particular kind of
>measure. However, I have had difficulty in finding a clear definition.
>This is made more difficult because of the more common use of
>"metric" as an adjective denoting the system of measurement units.
>Please
Helena wrote:
>I am looking for the formula of the hypergeometric distribution
>generalized to the multivariate hypergeometric distribution and
>I've have some problems to find some description of this matter,
>can anyone help me?
http://www.math.uah.edu/stat/urn/urn4.html
==
I thought readers of sci.stat.edu might be interested in this book. For
more information please visit
http://mitpress.mit.edu/catalog/item/default.asp?sid=5CEC3656-296C-4C48-B6E3-6BDFAC7EBADD&ttype=2&tid=3847
Best,
Jud
Advanced Mean Field Methods
Theory and Practice
edited by Manfred Opper and
I thought readers of sci.stat.edu might be interested in this book. For
more information please visit
http://mitpress.mit.edu/catalog/item/default.asp?sid=5CEC3656-296C-4C48-B6E3-6BDFAC7EBADD&ttype=2&tid=3847
Advanced Mean Field Methods
Theory and Practice
edited by Manfred Opper and David Saad
I thought readers of sci.stat.edu might be interested in this book. For
more information please visit
http://mitpress.mit.edu/catalog/item/default.asp?sid=5CEC3656-296C-4C48-B6E3-6BDFAC7EBADD&ttype=2&tid=3847
Best,
Jud
Advanced Mean Field Methods
Theory and Practice
edited by Manfred Opper and
I suggest that you use the P-values from the full-sample
fit.
Do know that proportion correctly classified is an
improper scoring rule, i.e., it can easily be
optimized by a model that in most other ways is
inferior, especially by a model that is very
poorly calibrated. One can add a significant
I would like to say, 'on the contrary,' but I'm not contradicting Eric
and the others' comments RE: "you don't calculate r^2 with insufficient
data."
If the number of observations equals the number of terms in the (regression)
model you do have a perfect fit, with no df, etc. This data is, nonet
Dear colleagues
I am looking for the formula of the hypergeometric distribution
generalized to the multivariate hypergeometric distribution and I've
have some problems to find some description of this matter, can anyone
help me?
Thanks in advance
best regards
Helena
=
Roberta Nacif wrote:
>
> To validate the logistic regression results, the logistic regression
> classifiers were trained on 9 folds and tested on 1 fold. This was
> performed 10 times, each time using other training and testing folds.
> Hence, I obtained 10 p-values and coefficients for each in
In sci.stat.consult Atul <[EMAIL PROTECTED]> wrote:
: I have a doubt regarding adjusted r-square
: How do we calculate the adjusted r-square when the error degrees of
: freedom are zero ?
You don't. you will have perfect prediction even for random numbers.
=
If the least-squares regression algorithm does not
"REQUIRE THE NUMBER OF OBSERVATIONS TO EXCEED
THE NUMBER OF PREDICTORS, THEN THE REGRESSION
ALGORITHM COULD BE USED TO SOLVE A SYSTEM OF
SIMULTANEOUS EQUATIONS THAT WOULD HAVE
NO ERRORS."
Another "interesting" characteristic of Excel Regression i
In sci.stat.consult Graeme Byrne <[EMAIL PROTECTED]> wrote:
> In short, you don't. If the number of terms in the model equals the number
> of observations you have much bigger problems than not being able to compute
> adjusted R^2. It should always be the case that the number of observations
> exc
[EMAIL PROTECTED] (Marg) wrote in message
news:<[EMAIL PROTECTED]>...
> Greetings..
> Can anyone suggest me what are the differences between Box and Jenkin
> Transfer function model and multiple regression model?
> Are there any good tutorials or freewares that deal with the Box and
> Jenkin Tran
In short, you don't. If the number of terms in the model equals the number
of observations you have much bigger problems than not being able to compute
adjusted R^2. It should always be the case that the number of observations
exceed the number of terms in the model otherwise you cannot calculate
Dear List members,
I am studying customers' repatronage decisions using logistic regression
and
tobit.
I analysed a data set of 516 observations (516 customers' purchasing
history
and survey measures) using 10 fold cross-validation and logistic
regression.
To validate the logistic regression res
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