similar to: nlme: New variance function structure varConstProp

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

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

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

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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

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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

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

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

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

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

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

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

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

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

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

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

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

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

Dear R users, I would like to perform Latent Class Logit Models for the analysis of choice experiments in environmental valuation. This kind of analysis is usually performed with NLogit Software (http://www.limdep.com). I attach the results I usually obtain using NLogit and NLogit model specifications. For Random parameter models and Logit Models I usually perform my analysis with the package