Ajay,
Bayesm deals with this very issue in choice modelling (a form of econometric
modelling as outlined in the article). I think those guys (the developers of
Bayesm) and the apprach they recommend for navigating the likelihood function
through a bayesian approachs makes a lot of sense to
Soren,
It sounds like you are new to R so I will refer you to some packages that I
think some people would find more user friendly as beginners.
Zelig is excellent. You could run a series of logistic regressions coding your
dependent variables as follows (a versus b, a versus c, b versus c)
Hi Richard,
It is if you use Rattle. Rattle allows you to do that for quite a few types
of models and has a really nice GUI interface. It has been developed for
the purposes of datamining, and given your use of the term score in your
post, I assume in part that this is what you are looking
Hi all,
I am getting the following error message.
Does somebody know what needs to happen here?
I have tried re-installing the RGtk2 package and also downloading a .dll
file and installing it in the RGtk2 file folder
Error in dyn.load(x, as.logical(local), as.logical(now)) :
unable
Hi Felipe,
Daniel mentions imputation is a disputed practice. There are
recommendations and rules of thumb for its use. I am not sure that
imputation is disputed. I would be interested to see some links to articles
recommending against its use.
Paul
- Original Message -
From:
okay,
when you cluster information, you can have two inputs
raw data information which the algorithms converts have into a matrix and
then processes
a pre-processed matrix which you create yourself to input into a package
essentially, packages will have a default assumption about the data
alg-design will do the trick
regards paul
- Original Message -
From: Caio Azevedo [EMAIL PROTECTED]
To: R - discussion list [EMAIL PROTECTED]
Sent: Monday, April 28, 2008 11:11 PM
Subject: [R] Fractional Factorial Design
Hi all,
Does anybody know if it is possible to build a
Caio,
using algdesign code below (this produces a full factorial 2*3*3 full
design)
gen.factorial(c(2,3,3))
X1 X2 X3
1 -1 -1 -1
2 1 -1 -1
3 -1 0 -1
4 1 0 -1
5 -1 1 -1
6 1 1 -1
7 -1 -1 0
8 1 -1 0
9 -1 0 0
10 1 0 0
11 -1 1 0
12 1 1 0
13 -1 -1 1
14 1 -1 1
15
- Original Message -
From: S Ellison [EMAIL PROTECTED]
To: Caio Azevedo [EMAIL PROTECTED]; paulandpen
[EMAIL PROTECTED]; R - discussion list
[EMAIL PROTECTED]
Sent: Tuesday, April 29, 2008 1:48 AM
Subject: Re: [R] Fractional Factorial Design
Paul;
You asked
using
I would suggest reading this attachment below.
http://support.sas.com/techsup/technote/ts722d.pdf
OptFedreov is the go for you, you are correct.
I don't know of anybody who has come up with design principles in choice
modelling that apply to logit and probit models etc.
We all assume that
of yeah, and your design needs to account for main effects and interactions
if you intend to model them, so make sure to program that into algdesign as
well
- Original Message -
From: zubin [EMAIL PROTECTED]
To: r-help@r-project.org
Sent: Monday, April 21, 2008 9:59 PM
Subject: [R]
Faisal,
can you elaborate further on your conjoint design
there is bayesm which offers a hierarchical bayes approach to analysing
choice data
MLogit available through zelig (see below)
http://gking.harvard.edu/zelig/docs/index.html
MNP as a standalone package for the probit model
thanks
AMINA SHAHZADI,
The eternal question.
What I do is that I generate a range of solutions, profile them on variables
used to cluster the data into groups and any other information I have to
profile the cluster groups on and then present the solutions to a group of
others to assess
Hi,
I am trying to use AlgDesign and am partially successful
Two lines of code are taken from the help file
1. Line 1 (below) works fine
dat-gen.factorial(levels=3,nVars=3,varNames=c(A,B,C))
2. Line 2 (below) does not work fine
desD-optFederov(~quad(A,B,C),dat,nTrials=14,eval=TRUE)
Here is
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