A database of Chinese surnames and Chinese given names (1930-2008).
This database contains nationwide frequency statistics of
1,806 Chinese surnames and 2,614 Chinese characters used in given names,
covering about 1.2 billion Han Chinese population
(96.8% of the Han Chinese household-registered population
born from 1930 to 2008 and still alive in 2008).
This package also contains a function for computing multiple features of
Chinese surnames and Chinese given names for scientific research (e.g.,
name uniqueness, name gender, name valence, and name warmth/competence).

person(given = "François",  family = "Petitjean", role = "aut"),
person(given = "Matthieu",  family = "Herrmann",  role = c("aut", "com", "cre"), email = "matthieu.herrmann@monash.edu"),
person(given = "Christoph", family = "Bergmeir",  role = c("ctb"))  )
Learning the structure of graphical models from datasets with thousands of variables.
More information about the research papers detailing the theory behind Chordalysis is available at
<http://www.francois-petitjean.com/Research> (KDD 2016, SDM 2015, ICDM 2014, ICDM 2013).
The R package development site is <https://github.com/HerrmannM/Monash-ChoR>.
Suggests: graph (>= 1.52.0), Rgraphviz (>= 2.18.0)

Imports: rJava (>= 0.9.8), commonsMath, stats

Imports: rJava (>= 0.9.9), commonsMath, stats

Title: Processing Data from Lattes CV Files
Imports: XML, tools, ggplot2, plotly, rmarkdown, knitr, WriteXLS,
Description: Processes data from Lattes CV
(<http://lattes.cnpq.br/>) XML files. Extract, condition, and plot
lists of journal and conference papers, book chapters, books,

Author: Ryan Sermas <DecisionAnalystR@decisionanalyst.com>, assisted by
Author@R: c(person("Ryan", "Sermas", role = "aut", email =
Description: Implements an MCMC algorithm to estimate a hierarchical
multinomial logit model with a normal heterogeneity
distribution. The algorithm uses a hybrid Gibbs Sampler with a
random walk metropolis step for the MNL coefficients for each
unit. Dependent variable may be discrete or continuous.
Independent variables may be discrete or continuous with
optional order constraints. Means of the distribution of
heterogeneity can optionally be modeled as a linear function of
Copyright: (C) 2011 Decision Analyst, Inc. (ChoiceModelR is a trademark
Packaged: 2012-01-03 19:39:08 UTC; CORP\jcolias