Provides functions to download and parse information from INEGI
(Official Mexican statistics agency). To learn more about the API, see <https://www.inegi.org.mx/servicios/api_indicadores.html>.
zoo, XML, plyr, jsonlite, lubridate, tibbletime

Measuring inequality, concentration and poverty
Inequality, concentration and poverty measures
Lorenz curves (empiric and theoretic)

Inequality, concentration and poverty measures
Lorenz curves (empirical and theoretical)

Measuring Inequality, Concentration, and Poverty
Inequality, concentration, and poverty measures. Lorenz
curves (empirical and theoretical).
R (>= 2.10.0), stats, graphics, grDevices

c(person(given = "Achim", family = "Zeileis", role = c("aut", "cre"), email = "Achim.Zeileis@R-project.org"),
person(given = "Christian", family = "Kleiber", role = "ctb", email = "Christian.Kleiber@unibas.ch"))
Inequality, concentration, and poverty measures. Lorenz curves (empirical and theoretical).
Achim Zeileis [aut, cre],
Christian Kleiber [ctb]

R (>= 2.1.0), stats, graphics, grDevices

c(person("Alberto", "Arcagni", role = c("aut", "cre"), email = "alberto.arcagni@uniroma1.it"), person("Igor", "Valli", role = c("aut"), email = "igor.valli@unibg.it"), person("Michele", "Zenga", role = c("ctb")))
Alberto Arcagni [aut, cre],
Igor Valli [aut],
Michele Zenga [ctb]
Computes and decomposes Gini, Bonferroni and Zenga 2007 point and synthetic concentration indexes. Decompositions are intended: by sources, by subpopulations and by sources and subpopulations jointly. References, Zenga M. M.(2007) <doi:10.1400/209575> Zenga M. (2015) <doi:10.1400/246627> Zenga M., Valli I. (2017) <doi:10.26350/999999_000005> Zenga M., Valli I. (2018) <doi:10.26350/999999_000011>.

Performing Inference on Networks with Regularization
Lourens Waldorp <waldorp@uva.nl>, Jonas Haslbeck <jonashaslbeck@gmail.com>
Performs inference with the lasso in Gaussian Graphical Models. The package consists of wrappers for functions from the 'hdi' package.

implements a network partitioning algorithm to identify communities (or modules) in a network. A network plotting function utilizes the identified community structure to position the vertices for plotting. The package also contains functions to calculate the assortativity and transitivity of a vertex.