Package: localgauss 0.41

Tore Selland Kleppe

localgauss: Estimating Local Gaussian Parameters

Computational routines for estimating local Gaussian parameters. Local Gaussian parameters are useful for characterizing and testing for non-linear dependence within bivariate data. See e.g. Tjostheim and Hufthammer, Local Gaussian correlation: A new measure of dependence, Journal of Econometrics, 2013, Volume 172 (1), pages 33-48 <doi:10.1016/j.jeconom.2012.08.001>.

Authors:Tore Selland Kleppe <tore.kleppe@uis.no>

localgauss_0.41.tar.gz
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localgauss.pdf |localgauss.html✨
localgauss/json (API)

# Install 'localgauss' in R:
install.packages('localgauss', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortranopenblas

1.48 score 1 packages 319 downloads 1 mentions 3 exports 32 dependencies

Last updated 3 years agofrom:a1b52003d8. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-linux-x86_64OKMar 13 2025
R-4.4-linux-x86_64OKMar 13 2025

Exports:localgausslocalgauss.indtestplot.localgauss

Dependencies:clicodetoolscolorspacefansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

Citation

To cite localgauss in publications use:

Geir Drage Berentsen, Tore Selland Kleppe, Dag Tjostheim (2014). Introducing localgauss, an R Package for Estimating and Visualizing Local Gaussian Correlation. Journal of Statistical Software, 56(12), 1-18. URL https://doi.org/10.18637/jss.v056.i12

Corresponding BibTeX entry: 

  @Article{,
    title = {Introducing {localgauss}, an {R} Package for Estimating
      and Visualizing Local Gaussian Correlation},
    author = {Geir Drage Berentsen and Tore Selland Kleppe and Dag
      Tj{\o}stheim},
    journal = {Journal of Statistical Software},
    year = {2014},
    volume = {56},
    number = {12},
    pages = {1--18},
    url = {https://doi.org/10.18637/jss.v056.i12},
  }