Hello,
I am using the locfit to fit a non parametric glm model to data with a gamma
distributed response variable. In the parametric glm regression the diagnostics
were based on the study of the standardized deviance or pearson residuals. How
can I estimate the the standardized Pearson
Hello! I am having a problem understanding what the weights option in
the locfit command of the locfit package is doing. I
have written a sample program which illustrates the issue (below). The
example involves using bootstrap however, that is not my main
goal but it illustrates where my problem
Hi,
Can you provide me an example in R to estimate the density using locfit package
with the help of multi dimensional explanatory variables and one dimensional
dependent variable?
Thank you.
Arnab Kumar Maity
Research Assistant
Indian School of Business
Hyderabad, India
DISCLAIMER:\ This
On Jul 6, 2010, at 7:08 AM, Arnab Maity wrote:
Hi,
Can you provide me an example in R to estimate the density using
locfit package with the help of multi dimensional explanatory
variables and one dimensional dependent variable?
When I came up with a solution I posted it:
Of Keith Jewell
Sent: Thursday, February 25, 2010 4:11 AM
To: r-h...@stat.math.ethz.ch
Subject: [R] locfit: max number of predictors?
Hi All,
In another thread Andy Liaw, who CRAN lists as locfit
maintainer; said:
quote
From: Liaw, Andy andy_l...@merck.com
To: Guy Green guygr...@netvigator.com
Hi All,
In another thread Andy Liaw, who CRAN lists as locfit maintainer; said:
quote
From: Liaw, Andy andy_l...@merck.com
To: Guy Green guygr...@netvigator.com; r-help@r-project.org
Subject: Re: Alternatives to linear regression with multiple variables
Date: 22 February 2010 17:50
You can try
Just replacing preplot() with predict() should be fine.
BTW, it's always a good idea to specify the version of the package
you're using as well.
Best,
Andy
From: mh...@berkeley.edu
Hi,
I'm trying to work through the examples and code in Loader's
LOCAL REGRESSION AND LIKELIHOOD, and have
Hi,
I'm trying to work through the examples and code in Loader's
LOCAL REGRESSION AND LIKELIHOOD, and have run into a problem
with the code for one sided smoothing and change point analysis
(p. 110-112).
The code, after loading locfit:
midp-(1945:1988)+0.5
fitl-locfit(thickness~left(year),
On Tue, 03 Mar 2009 22:10:42 +0100, David Winsemius
dwinsem...@comcast.net wrote:
That is what I thought to be the critical paragraph. The variance is
assumed to be = 1 when you use family=gaussian rather than the default
of family=qgauss. You give it a vector, 1000*rnorm(100), that ranges
Dear all,
I just realized that using family=qgauss restores normal-looking
confidence bands... I read that using family=gaussian rather than
family=qgauss fixes the dispersion parameter at 1, but without knowing
the theory behind the code, I dont understand why there is such a
I think you should read (or re-read) the locfit help page and *also*
the links from that page to the help pages for locfit.raw and rv. I
would have thought that since family= is not an argument to locfit per
se, but rather is documented in locfit.raw that you have yet done so,
but perhaps
From: Suresh Krishna
[...]
ps. The package maintainer, Catherine Loader, is no longer
reachable at
her Auckland address.
For the record, I'm the package maintainer for locfit, and I have not
exactly vanished (yet). Please see the package description.
That said, it doesn't mean I know all
David Winsemis wrote:
I think you should read (or re-read) the locfit help page and *also*
the links from that page to the help pages for locfit.raw and rv. I
would have thought that since family= is not an argument to locfit per
se, but rather is documented in locfit.raw that you have
That is what I thought to be the critical paragraph. The variance is
assumed to be = 1 when you use family=gaussian rather than the
default of family=qgauss. You give it a vector, 1000*rnorm(100),
that ranges widely and a small (relative) variance is assumed and so
the confidence intervals
I have been using some old R scripts that were prepared for me using
R Version 1.9.0. In these, there is a call to
library(locfit)
and with this version of R, I have no problem.
But needing to upgrade to the latest version of R, I find these
scripts no longer work, and with
help(locfit)
I
My guess is that you have not configured you new installation to see
(and update) your collection of packages. As a quick fix, what happens
when you go to your favorite CRAN mirror and install a new copy of
locfit? My version is 1.5-4 and runs with recent versions of R.
--
David Winsemius,
Hello all!
I have recently started using the LOCFIT package, together with Clive
Loader's book. I need to implement some method for automatic (plug-in)
bandwidth selection in a multivariate kernel regression. From the book, and
the LOCFIT documentation, it is not clear whether this is
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