Displaying 20 results from an estimated 70 matches similar to: "nlme: New variance function structure varConstProp"
2020 Jul 20
1
Methods for objects inheriting from lme (nlme package)
Dear R developers,
One function in my mkin package [1] returns an object that is originally
created by nlme(), but contains some additional information. Its class is
c("mmkin.nlme", "nlme", "lme").
Now I would like to use the anova() method for lme objects for comparing such
S3 objects. Unfortunately, anova.lme currently does not check for inheritance,
but
2009 Jul 31
1
colored 3D pillar plots
hi,
I'd like to do graphs like shown on the right panel on the following link:
http://www.clinchem.org/cgi/content/full/53/8/1544/F1
(if link doesn't work see attached file)
Any help and ideas highly appreciated, thanks in advance.
Thomas von K?nel
Human Genetics
Uni Berne
2008 Jul 23
1
[Fwd: Re: Coefficients of Logistic Regression from bootstrap - how to get them?]
I think the argument supporting the use of bootstrap to determine
coefficients, as opposed to just running linear regression on the whole
dataset, is the comparison of Rsq and prediction errors between these
two approaches - page 1502. There's a substantial difference in favor of
the bootstrap approach.
--
Michal J. Figurski
Gustaf Rydevik wrote:
> The url for the mentioned paper is
2010 Jul 18
6
CRAN (and crantastic) updates this week
CRAN (and crantastic) updates this week
New packages
------------
* allan (1.0)
Alan Lee
http://crantastic.org/packages/allan
Automates Large Linear Analysis Model Fitting
* andrews (1.0)
Jaroslav Myslivec
http://crantastic.org/packages/andrews
Andrews curves for visualization of multidimensional data
* anesrake (0.3)
Josh Pasek
http://crantastic.org/packages/anesrake
This
2019 Jul 04
2
Fwd: Fedora 31 System-Wide change proposal: Automatic R runtime dependencies
FYI, I plan on implementing this for F31 if no issues arise.
---------- Forwarded message ---------
From: Ben Cotton <bcotton at redhat.com>
Date: Tue, 2 Jul 2019 at 10:55
Subject: Fedora 31 System-Wide change proposal: Automatic R runtime dependencies
To: <devel-announce at lists.fedoraproject.org>, Development discussions
related to Fedora <devel at lists.fedoraproject.org>
2018 Oct 22
2
Chapuza total?? Crear web con R
Buenas Victor,
Gracias por el mail. Suele pasar lod e descubrir el paquete una vez que has terminado el curro.. jejejeje
Las webs estan bien, pero estaba pensando mase n webs de formularios..
No obstante, lo tomo en cuenta. Muchas gracias
Jes?s
________________________________
De: V?ctor Granda Garc?a <victorgrandagarcia en gmail.com>
Enviado: lunes, 22 de octubre de 2018 22:17
Para:
2019 May 29
0
Making a package CITATION file from BibTeX
On Thu, 30 May 2019, Dr Gregory Jefferis wrote:
> Dear Colleagues,
>
> I would like to provide a CITATION file for my package nat.nblast [1].
>
> I have the correct citation in BibTeX format [2]. How can I convert this
> BibTeX to the format needed by R for a package CITATION file (I have a
> lot of other packages needing citations ...).
(1) You can use read.bib() from the
2014 Dec 22
0
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2008 Jul 10
0
ppls: version 1.02 including a new data set
Dear R users,
an update of the package ppls - Penalized Partial Least Squares - is now
available on CRAN.
It implements the methods described in
N. Kr?mer, A.-L. Boulesteix, G. Tutz
"Penalized Partial Least Squares with Applications to B-Spline
Transformations and Functional Data"
Chem. Intell. Lab. Sys. 2008
http://dx.doi.org/10.1016/j.chemolab.2008.06.009
Features of the package
2008 Jul 10
0
ppls: version 1.02 including a new data set
Dear R users,
an update of the package ppls - Penalized Partial Least Squares - is now
available on CRAN.
It implements the methods described in
N. Kr?mer, A.-L. Boulesteix, G. Tutz
"Penalized Partial Least Squares with Applications to B-Spline
Transformations and Functional Data"
Chem. Intell. Lab. Sys. 2008
http://dx.doi.org/10.1016/j.chemolab.2008.06.009
Features of the package
2017 Aug 12
0
OHPL - new package for group variable selection
Dear useRs,
- I am pleased to announce that the R package OHPL is now available on
CRAN (https://CRAN.R-project.org/package=OHPL).
The package implements the ordered homogeneity pursuit lasso (OHPL)
algorithm for group variable selection proposed in Lin et al. (2017)
<doi:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the
homogeneity structure in high-dimensional data and enjoys
2012 Oct 26
0
colorspace: interactive HCL palette chooser
Dear useRs,
we have just released a new version (1.2-0) of the "colorspace" package:
http://CRAN.R-project.org/package=colorspace
In addition to the infrastructure for transforming colors between
different color spaces (RGB, HSV, HCL, and various others) and support for
different types of color palettes (qualitative, sequential, diverging),
there is now a new graphical user
2012 Oct 26
0
colorspace: interactive HCL palette chooser
Dear useRs,
we have just released a new version (1.2-0) of the "colorspace" package:
http://CRAN.R-project.org/package=colorspace
In addition to the infrastructure for transforming colors between
different color spaces (RGB, HSV, HCL, and various others) and support for
different types of color palettes (qualitative, sequential, diverging),
there is now a new graphical user
2017 Aug 12
0
OHPL - new package for group variable selection
Dear useRs,
- I am pleased to announce that the R package OHPL is now available on
CRAN (https://CRAN.R-project.org/package=OHPL).
The package implements the ordered homogeneity pursuit lasso (OHPL)
algorithm for group variable selection proposed in Lin et al. (2017)
<doi:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the
homogeneity structure in high-dimensional data and enjoys
2019 Sep 30
0
New package 'backbone' for extracting significant edges from a weighted graph
Hello R users,
I am excited to introduce a new package for R which is now available on CRAN called ?backbone?.
The package can be found here: https://cran.r-project.org/web/packages/backbone/index.html
The backbone package provides methods for extracting from a weighted graph a binary or signed backbone that retains only the significant edges. The user may input a weighted graph, or a bipartite
2019 Sep 30
0
New package 'backbone' for extracting significant edges from a weighted graph
Hello R users,
I am excited to introduce a new package for R which is now available on CRAN called ?backbone?.
The package can be found here: https://cran.r-project.org/web/packages/backbone/index.html
The backbone package provides methods for extracting from a weighted graph a binary or signed backbone that retains only the significant edges. The user may input a weighted graph, or a bipartite
2023 Apr 12
0
DNAmixturesLite and KinMixLite
Dear all,
We are pleased to announce that CRAN now hosts our packages
DNAmixturesLite and KinMixLite.
These are fully R-based versions of our packages DNAmixtures and KinMix,
which rely on a commercial software, HUGIN, for performing efficient
computations in Bayesian networks. The lite versions rely instead on
gRain for such computations.
DNAmixtures provides statistical methods for DNA
2023 Apr 12
0
DNAmixturesLite and KinMixLite
Dear all,
We are pleased to announce that CRAN now hosts our packages
DNAmixturesLite and KinMixLite.
These are fully R-based versions of our packages DNAmixtures and KinMix,
which rely on a commercial software, HUGIN, for performing efficient
computations in Bayesian networks. The lite versions rely instead on
gRain for such computations.
DNAmixtures provides statistical methods for DNA
2009 Jan 26
0
AdMit version 1-01.01
Dear all,
The new version of AdMit (version 1.01-01) is now available from CRAN.
SUMMARY
The package provides functions to perform the fitting of an adaptive
mixture of Student-t distributions to a target density through its
kernel function. The mixture approximation can then be used as the importance
density in importance sampling or as the candidate density in the
Metropolis-Hastings
2009 Jan 26
0
AdMit version 1-01.01
Dear all,
The new version of AdMit (version 1.01-01) is now available from CRAN.
SUMMARY
The package provides functions to perform the fitting of an adaptive
mixture of Student-t distributions to a target density through its
kernel function. The mixture approximation can then be used as the importance
density in importance sampling or as the candidate density in the
Metropolis-Hastings