Dear all,
Your constant talking about what bootstrap is and is not suitable for
made me finally verify the findings in the Pawinski et al paper.
Here is the procedure and the findings:
- First of all I took the raw data (that was posted earlier on this
list) and estimated the AUC values
Frank and all,
The point you were looking for was in a page that was linked from the
referenced page - I apologize for confusion. Please take a look at the
two last paragraphs here:
http://people.revoledu.com/kardi/tutorial/Bootstrap/examples.htm
Though, possibly it's my ignorance, maybe
On Thu, Jul 31, 2008 at 4:30 PM, Michal Figurski
[EMAIL PROTECTED] wrote:
Frank and all,
The point you were looking for was in a page that was linked from the
referenced page - I apologize for confusion. Please take a look at the two
last paragraphs here:
Gustaf,
Summarizing things I don't understand:
- Honestly, I was thinking I can use bootstrap to obtain better
estimate of a mean - provided that I want it. So, I can't?
- If I can't obtain reliable estimates of CI and variance from a small
dataset, but I can do it with bootstrap - isn't it a
Tim,
If I understand correctly, you are saying that one can't improve on
estimating a mean by doing bootstrap and summarizing means of many such
steps. As far as I understand (again), you're saying that this way one
can only add bias without any improvement...
Well, this is in contradiction
Michal Figurski wrote:
Tim,
If I understand correctly, you are saying that one can't improve on
estimating a mean by doing bootstrap and summarizing means of many such
steps. As far as I understand (again), you're saying that this way one
can only add bias without any improvement...
Well,
I'll address the question of whether you can use the bootstrap to
improve estimates, and whether you can use the bootstrap to virtually
increase the size of the sample.
Short answer - no, with some exceptions (bumping / Random Forests).
Longer answer:
Suppose you have data (x1, ..., xn) and a
-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Michal Figurski
Sent: Wednesday, July 23, 2008 10:22 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from
bootstrap - how to get them?
Thank you all for your words of wisdom.
I start getting
Of Michal Figurski
Sent: Thursday, July 24, 2008 8:03 AM
Cc: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap - how to
get them?
Greg and all,
Just another thought on bias and variability. As I tried to explain, I
perceive this problem as a very practical problem
-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap - how to
get them?
Greg and all,
Just another thought on bias and variability. As I tried to explain, I
perceive this problem as a very practical problem.
The equation, that is the goal of this work
--- On Thu, 7/24/08, Michal Figurski [EMAIL PROTECTED] wrote:
From: Michal Figurski [EMAIL PROTECTED]
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap - how to
get them?
To:
Cc: r-help@r-project.org r-help@r-project.org
Received: Thursday, July 24, 2008, 11:02 AM
Hi All,
It really comes down to a question of attitude: you either want to learn
something fundamental or core and so bootstrap yourself to a better place
(at least away from where you are), or you don't. As Marc said, Michal seems
to have erected a wall around his thinking.
I don't think it's
Thank you Gustaf,
I apologize for not including an example data in my first email.
Nevertheless, your code worked for me excellently - I only added 55 as
the size of sample.
I must admit this code looks so much simpler, compared to SAS. I am
beginning to love R, despite some disrespectful
It seems you have accidentally hit a surgeons' mailing list where all
you wanted was some advice how to use this scalpel on your body.
Sorry if we can't be of any help without intimidating you with
unrelated and pompous terms -- like coagulation.
Michal J. Figurski [EMAIL PROTECTED] [Wed, Jul 23,
On Wed, Jul 23, 2008 at 4:08 PM, Michal Figurski
[EMAIL PROTECTED] wrote:
Gustaf,
I am sorry, but I don't get the point. Let's just focus on predictive
performance from the cited passage, that is the number of values predicted
within 15% of the original value.
So, the predictive performance
Thank you all for your words of wisdom.
I start getting into what you mean by bootstrap. Not surprisingly, it
seems to be something else than I do. The bootstrap is a tool, and I
would rather compare it to a hammer than to a gun. People say that
hammer is for driving nails. This situation is
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Michal Figurski
Sent: Wednesday, July 23, 2008 10:22 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from
bootstrap - how to get them?
Thank you all for your words
Gustaf Rydevik wrote:
On Wed, Jul 23, 2008 at 4:08 PM, Michal Figurski
[EMAIL PROTECTED] wrote:
Gustaf,
I am sorry, but I don't get the point. Let's just focus on predictive
performance from the cited passage, that is the number of values predicted
within 15% of the original value.
So, the
Michal Figurski wrote:
Thank you all for your words of wisdom.
I start getting into what you mean by bootstrap. Not surprisingly, it
seems to be something else than I do. The bootstrap is a tool, and I
would rather compare it to a hammer than to a gun. People say that
hammer is for driving
Dear all,
I don't want to argue with anybody about words or about what bootstrap
is suitable for - I know too little for that.
All I need is help to get the *equation coefficients* optimized by
bootstrap - either by one of the functions or by simple median.
Please help,
--
Michal J.
:[EMAIL PROTECTED] On Behalf Of Michal Figurski
Sent: Tuesday, July 22, 2008 9:52 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from
bootstrap - how to get them?
Dear all,
I don't want to argue with anybody about words or about what
bootstrap is suitable
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from
bootstrap - how to get them?
Dear all,
I don't want to argue with anybody about words or about what
bootstrap is suitable for - I know too little for that.
All I need is help to get the *equation coefficients
: [R] Coefficients of Logistic Regression from
bootstrap - how to get them?
Hmm...
It sounds like ideology to me. I was asking for technical
help. I know what I want to do, just don't know how to do it
in R. I'll go back to SAS then. Thank you.
--
Michal J. Figurski
Doran, Harold
Hi Michal,
This paper by John Fox may help you to precise what you are looking for and
to perform your analyses
http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-bootstrapping.pdf
Nael
On Tue, Jul 22, 2008 at 3:51 PM, Michal Figurski
[EMAIL PROTECTED] wrote:
Dear all,
I don't want
, 2008 9:52 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from
bootstrap - how to get them?
Dear all,
I don't want to argue with anybody about words or about what
bootstrap is suitable for - I know too little for that.
All I need is help to get
(which is what bootstrap is for) then you
are on your own.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Michal Figurski
Sent: Tuesday, July 22, 2008 9:52 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap
: Tuesday, July 22, 2008 9:52 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from
bootstrap
- how to get them?
Dear all,
I don't want to argue with anybody about words or about what
bootstrap is suitable for - I know too little for that.
All
.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Michal Figurski
Sent: Tuesday, July 22, 2008 9:52 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap
- how to get them?
Dear all,
I don't want to argue with anybody about
PROTECTED] On Behalf Of Michal Figurski
Sent: Tuesday, July 22, 2008 9:52 AM
To: r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap
- how to get them?
Dear all,
I don't want to argue with anybody about words or about what
bootstrap is suitable for - I know
Hello all,
I am trying to optimize my logistic regression model by using bootstrap.
I was previously using SAS for this kind of tasks, but I am now
switching to R.
My data frame consists of 5 columns and has 109 rows. Each row is a
single record composed of the following values:
Michal Figurski wrote:
Hello all,
I am trying to optimize my logistic regression model by using bootstrap.
I was previously using SAS for this kind of tasks, but I am now
switching to R.
My data frame consists of 5 columns and has 109 rows. Each row is a
single record composed of the
Frank,
How does bootstrap improve on that?
I don't know, but I have an idea. Since the data in my set are just a
small sample of a big population, then if I use my whole dataset to
obtain max likelihood estimates, these estimates may be best for this
dataset, but far from ideal for the whole
I used bootstrap to virtually increase the size of my
dataset, it should result in estimates more close to that
from the population - isn't it the purpose of bootstrap?
No, not really. The bootstrap is a resampling method for variance
estimation. It is often used when there is not an easy
Hi Doran,
Maybe I am wrong, but I think bootstrap is a general resampling method which
can be used for different purposes...Usually it works well when you do not
have a presentative sample set (maybe with limited number of samples).
Therefore, I am positive with Michal...
P.S., overfitting, in
; r-help@r-project.org
Subject: Re: [R] Coefficients of Logistic Regression from bootstrap -
how to get them?
Hi Doran,
Maybe I am wrong, but I think bootstrap is a general resampling method
which can be used for different purposes...Usually
Michal Figurski wrote:
Frank,
How does bootstrap improve on that?
I don't know, but I have an idea. Since the data in my set are just a
small sample of a big population, then if I use my whole dataset to
obtain max likelihood estimates, these estimates may be best for this
dataset, but far
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