Package: poweRlaw
Type: Package
Title: Fitting heavy tailed distributions: the poweRlaw package
Version: 0.20.0
Date: 2013-06-05
Authors@R: person("Gillespie", "Colin",
        email="colin.gillespie@newcastle.ac.uk", role = c("aut",
        "cre"))
Author: Colin Gillespie
Maintainer: Colin Gillespie <colin.gillespie@newcastle.ac.uk>
Description: This package implements both the discrete and continuous
        maximum likelihood estimators for fitting the power-law
        distribution to data.  Additionally, a goodness-of-fit based
        approach is used to estimate the lower cut-off for the scaling
        region.
URL: https://github.com/csgillespie/poweRlaw
BugReports: https://github.com/csgillespie/poweRlaw/issues
Depends: stats, R (>= 2.15.0)
Imports: VGAM, parallel, methods
License: GPL-3
Collate: 'aaa_all_classes.R' 'all_classes_ctn.R'
        'all_classes_discrete.R' 'AllGenerics.R' 'bootstrap_p.R'
        'bootstrap.R' 'ctn_helper_functions.R' 'data_help_files.R'
        'discrete_helper_functions.R' 'dist_cdf-methods.R'
        'dist_data_cdf-methods.R' 'dist_ll-methods.R'
        'dist_pdf-methods.R' 'dist_rand-methods.R' 'estimate_pars.R'
        'estimate_xmin.R' 'initialize-methods.R' 'lines-methods.R'
        'mle-methods.R' 'plcon.R' 'pldis.R' 'plot-methods.R'
        'points-methods.R' 'poweRlaw-package.R' 'checks.R'
        'compare_distributions.R'
Packaged: 2013-06-07 09:12:43 UTC; ncsg3
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-06-07 11:31:06
