this should be possible in the lasso2 package.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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On Sep 7
You might look at the monotone fitting available in the rqss()
function of the quantreg package.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax: 217-244
If you want to minimize absolute error for this, then you can
try the rqss fitting in the quantreg package and tune lambda
to get one break in the fitted function.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217
You could use:
require(quantreg)
rq(index ~ 1, weights=count, tau=0:5/5)
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-6678
You might want to look at the cartogram literature. See e.g.
http://www-personal.umich.edu/~mejn/election/
I don't know of an R implementation of this sort of thing, but
perhaps others can correct me.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED
One way:
N - 10
s - c(apply(matrix(rep(1:3,N),3,N),2,sample))
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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If you are willing to go to the bother of representing your data
as a sparse matrix, the package SparseM has a version of image()
that will do what you would like to do, I believe.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department
to be
fitting
a mean curve to data that has constant variance, so you might also
consider reweighting to approximate this, as well.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University
(slmobj)
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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On Aug 1, 2007, at 4:42 PM, T. Balachander wrote
: you can always modify
functions
such as summary.rq or plot.summary.rqs -- see for example ?fix.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
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size exceeds 1001, or cov = FALSE in which case se =
nid is used.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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and to Martin Maechler for adding this dataset to R.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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On Jul 24, 2007
to introduce new errors that can't be tracked down at later
stages of the analysis.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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knows exactly what to do with ratfor provided you have the
ratfor preprocessor available from the above link, and the rest
of the tools to build from source.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558
You might try: http://www.stanford.edu/~kasparr/software/silverman.r
But take a look at the referenced paper by Silverman first. You could
also try the CRAN package ftnonpar by Kovac and Davies.
url:www.econ.uiuc.edu/~roger/my.htmlRoger Koenker
email [EMAIL PROTECTED
You might have a look at the fda package of Ramsay on CRAN.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
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estimated the fixed effects with the
sweep operation.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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On May 5
Ivo,
I don't know whether you ever got a proper answer to this question.
Here is a kludgy one -- someone else can probably provide
a more elegant version of my diffid function.
What you want to do is sweep out the mean deviations from both y
and x based on the factor fe and then estimate the
of this, and if so, why the former version was
preferred. The
latter version seems more convenient since it obviously obviates the
need
for special tables that appear in many places.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department
If you can reformulate your LP as an L1 problem, which is known to be
possible without loss of generality, but perhaps not without loss of
sleep,
then you could use the sparse quantile regression functions in the
quantreg package.
url:www.econ.uiuc.edu/~rogerRoger Koenker
a shot at it. My first attempt is
rather primitive
but I have to say that Paul's grid package is superb.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University
It's not often one gets needs to correct Gabor, but no,
least median of squares is not the same as least absolute error
regression.
Take a look at the package robust if you want the lms.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED
both Matrix and SparseM have formats of this type.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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If you haven't already you might want to take a look at:
http://www.econ.uiuc.edu/~roger/research/rq/QReco.pdf
which is written by and for ecologists.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217
Doug is right, I think, that this would be easier with full indexing
using the matrix.coo classe, if you want to use SparseM. But
then the tapply seems to be the way to go.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
() to define the X matrix directly. This is usually
not that
difficult, but it depends on the model
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University
quantile() does some somewhat exotic interpolation --- if you are
wanting to
match moments you need to be more explicit about how you are computing
moments for the two approaches...
On Jan 28, 2007, at 5:06 PM, Geoffrey Zhu wrote:
Hi Benilton,
I tried this. It sort of works, but the results
to use them.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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On Jan 10, 2007, at 12:23 PM, Kati Schweitzer
Is there a painless way to find the names of all packages on CRAN
that Depend on a specified package?
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
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On Jan 1, 2007, at 4:43 PM, Armelini, Guillermo wrote:
Hello everyone
Could anybody tell me how to set the following matrix?
n2-matrix(nrow=10185,ncol=10185,seq(0,0,length=103734225))
You can use:
library(SparseM)
as.matrix.coo(0,10185,10185)
but then you need to find something
, and maintaining
a fixed, linear
in parameters specification for the covariate effects at each quantile.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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with additive models
using total variation as a roughness penalty for nonlinear terms.
Another, along more tree structured lines, is Nicolai Meinshausen's
quantregforest package.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of roger koenker
Sent: Wednesday
This isn't a nonlinear QR problem. You can write:
f - rq(y ~ log(x), data=Dat, tau=0.25)
which corresponds to the model
Q_y (.25|x) = a log(x) + b
note the sign convention on b.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED
that is more automatic.
Does anyone have experience that they could share toward this objective?
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-6678
:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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On Oct 27, 2006, at 11:52 AM, Gabor Grothendieck wrote:
I don't
for
microarrays that have
incorporated these effects.
I'd be happy to hear more about the data and possible models, but
this should be
routed privately since the topic is rather too specialized for R-help.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED
data(engel)
attach(engel)
rq(y~x)
Call:
rq(formula = y ~ x)
Coefficients:
(Intercept) x
81.4822474 0.5601806
Degrees of freedom: 235 total; 233 residual
rq(y~x)-f
f$tau
[1] 0.5
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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On Oct 12, 2006, at 7:12 AM, Roger Bivand wrote
diagnostic. Thanks,
Roger
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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Try:
rsimplex - function(n){
u - diff(sort(runif(n)))
c(u,1-sum(u))
}
On Oct 2, 2006, at 5:43 PM, Rolf Turner wrote:
Ricardo Rios wrote:
Hi Rolf Turner, I have a statistical model, it model need this
numbers for calculate the probability. This numbers must be random.
For example I need
?rle
url:www.econ.uiuc.edu/~rogerRoger Koenker
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On Sep 30, 2006
Or, perhaps, tripack?
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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On Sep 14, 2006, at 10:32 AM, Greg
Look at ?rank ?order and ?quantile assuming that you are using
these terms as in cs.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
fax
General questions elicit general answers; more specific questions
elicit more specific answers.For example,
exp(2+9/2)
[1] 665.1416
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558
I would suspect that something simple like
sum(diag(crossprod(A,B)))
would be quite competitive...
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax
for that matter, so it isn't likely to
be automatically provided in quantreg any time soon.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-6678Champaign, IL 61820
On Aug 2, 2006, at 4:01 PM, John Kane wrote:
Simple problem but I don't see
On Jul 23, 2006, at 5:27 AM, roger koenker wrote:
When computing the median from a sample with an even number of
distinct
values there is inherently some ambiguity about its value: any
value between
the middle order statistics is a median. Similarly, in
regression settings
. The quantile
regression fitting
functions don't understand about singular designs; some day they may
but it isn't
a high priority for me.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558
Roger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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__
R-help
Questions about packages should be directed to the package maintainers.
A more concise example of the difficulty, with accessible data would
also be helpful.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox
You need to look at the packages specifically designed for
sparse matrices: SparseM and Matrix.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University
seconds with again 93% of the total time spent in
rnorm and rtnorm...
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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depressing ritual of returning exam
results. Full disclosure of the distribution in a very concise
encoding.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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, of course, that it is really a question about
quantreg.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-6678Champaign, IL 61820
On Jun
amount
to setting singular.ok = FALSE in lm() and forcings users to do
the rank reduction themselves.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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sparse linear algebra and realized that virtually all
large problems that I was interested in were better handled in from
that perspective.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558
an upgrade: from the flintstones -- to the michelin man...
On May 16, 2006, at 4:40 PM, Thomas Lumley wrote:
On Tue, 16 May 2006, roger koenker wrote:
In ancient times, 1999 or so, Alvaro Novo and I experimented with an
interface to mysql that brought chunks of data into R
?in.convex.hull in the package tripack.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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On Apr 26
Powell's quantile regression method is available in the quantreg
package rq(..., method=fcen, ...)
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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Roger Koenker
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vox: 217-333-4558University of Illinois
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On Apr 24, 2006, at 12:41 PM, Sachin J wrote:
Hi,
I have a dataset consisting of 350,000 rows
:www.econ.uiuc.edu/~rogerRoger Koenker
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On Mar 16, 2006, at 6:13 AM, Liaw, Andy wrote:
loess() should
) 1 1 2 3 5
Degrees of freedom: 5 total; 4 residual
The first observation x=1 has weight .33 so it should be the
.25 quantile, unless there is some interpolation going on
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED
a strategy for this that I use is just
persp(interp(x,y,z))
where interp is from the Akima package, and x,y,z are all
of the same length.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558
function?
package: quantreg
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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On Feb 6, 2006, at 2:34 PM, ivo welch wrote:
Aside, a logical ordering might also be:
mean sd min q1 med q3 max
rather than have mean buried in between order statistics.
Just where it belongs, IMHO
url:www.econ.uiuc.edu/~rogerRoger Koenker
email
Roger Koenker
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On Jan 19, 2006, at 6:04 AM, Achim Zeileis wrote:
On Thu, 19 Jan 2006 14:05:58 +0530 Ajay Narottam
see ?rle
url:www.econ.uiuc.edu/~rogerRoger Koenker
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On Jan 12, 2006, at 9:56 AM, Mark Leeds wrote
to the discussion at:
http://bugs.r-project.org/cgi-bin/R/Models?id=1861;user=guest
but in any case I hope that someone can suggest how such
difficulties can be circumvented.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox
see ?anova.glm
On Dec 18, 2005, at 10:32 AM, David STADELMANN wrote:
Hi,
I am running glm logit regressions with R and I would like to test a
linear combination of coefficients (H0: beta1=beta2 against H1:
beta1beta2). Is there a package for such a test or how can I perform
it otherwise
(quantreg)
formula - log(y) ~ x
plot(x,y)
z - 1:30/10
for(tau in 10:19/20){
f - rq(formula,tau = tau)
lines(z,exp(cbind(1,z) %*% f$coef))
}
url:www.econ.uiuc.edu/~rogerRoger Koenker
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project for one of
you who like using ; ?
Roger
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
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you can do:
X - model.matrix(formula, data = your.data)
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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you might consider nlrq() in the quantreg package, which does median
regression for nonlinear response functions
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558
.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of
Economics
vox:217-333-4558University of Illinois
fax:217-244-6678Champaign, IL 61820
to sparse representation
to decide what is really zero -- by default this is eps = .Machine
$double.eps.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department of Economics
vox: 217-333-4558University of Illinois
fax
/~rogerRoger Koenker
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vox: 217-333-4558University of Illinois
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__
R-help@stat.math.ethz.ch mailing list
are
available in the vignette for the quantreg package.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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a 64 bit build
but never encounter such problems, and I don't see anything in the
archives or the
install manual that is relevant -- but of course, I'm not very clear
about what I'm looking
for either.
Roger
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED
but presumably just needs -L/usr/openwin/lib/sparcv9. Some further
investigation is needed for png, jpeg and tctlk support, but this can
wait
for a little while.
Thanks very much for your help.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EMAIL PROTECTED]Department
segments not 3, but this can be controlled by the choice
of lambda in the qss
function, for example, try:
fit - rqss(y ~ qss(x,lambda=3)
plot(fit,col=red)
which gives a fit like you suggest might be reasonable with only
three segments.
url:www.econ.uiuc.edu/~rogerRoger
On May 6, 2005, at 2:45 PM, Roger Bivand wrote:
On Fri, 6 May 2005, m p wrote:
Hello,
I'd like to make a z(x,y) plot for irregularly spaced
x,y. What are routines are available in R for this
purpose?
One possibility is to interpolate a regular grid using interp() in the
akima package, then use
For my money, Frank's comment should go into fortunes. It seems a
rather Sisyphean battle to keep the lessons of robustness on the
statistical table
but nevertheless well worthwhile.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED
Wayne Fuller's Measurement Error Models is a good reference.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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The dense blocks are too big as Reid has already written --
for smaller instances of this sort of thing I would suggest that the
the kronecker
product %x% operator in SparseM, would be more convenient.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED
:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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my favorite answer to this question is because there is no one to sue.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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On Mar 2, 2005, at 6:25 PM, Vadim Ogranovich wrote:
I was recently plowing through the docs of the quantreg package by
Roger
Koenker and came across the total variation penalty approach to
1-dimensional spline fitting. I googled around a bit and have found
some
papers originated in the image
Just for the record -- NEWS for 2.1.0 includes:
o binomial() has a new cauchit link (suggested by Roger Koenker).
the MASS polr for ordered response is also now adapted for the Cauchit
case.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED
-parameter
log-normal where one gets an unbounded likelihood by letting the
threshold parameter approach the first order statistic from below, but
for which the likeihood equations seem to provide a perfectly sensible
root.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email
Don't you want read.matrix.csr not read.matrix?
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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a full fledged browser. Lynx is ok for this purpose,
but it
might be nice to have something more specifically designed for CIS.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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vox:217-333-4558
?) about the R - R case.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
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On Dec
Roger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
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On Dec 1, 2004, at 10:56 AM, James Foadi wrote:
On Wednesday 01
At the risk of stirring up a hornet's nest , I'd suggest that
means are dangerous in such applications. A nice paper
on combining ratings is: Gilbert Bassett and Joseph Persky,
Rating Skating, JASA, 1994, 1075-1079.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email
lower triangle can be obtained by
A[row(A)col(A)]
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of
searching
for a forgotten function would be grateful.
url:www.econ.uiuc.edu/~rogerRoger Koenker
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?interp in akima for f: R^2 - R.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
fax:217-244-6678Champaign
this seems
to be overkill... standard mle methods should be preferable. (??)
Googling reveals that spss provides such functions... just to wave a red
flag.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217
be reasonably quick.
HTH
url:www.econ.uiuc.edu/~rogerRoger Koenker
email [EMAIL PROTECTED] Department of Economics
vox:217-333-4558University of Illinois
fax:217-244-6678Champaign, IL 61820
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