XML, tools, ggplot2, plotly, rmarkdown, knitr, WriteXLS,
utils, grDevices, R.utils
Processes data from Lattes CV
(<http://lattes.cnpq.br/>) XML files. Extract, condition, and plot
lists of journal and conference papers, book chapters, books,
and more.

Ryan Sermas <DecisionAnalystR@decisionanalyst.com>, assisted by
John V. Colias <DecisionAnalystR@decisionanalyst.com>
c(person("Ryan", "Sermas", role = "aut", email =
"DecisionAnalystR@decisionanalyst.com), person("John",
"Colias", "V", role = "ctb", email =
"DecisionAnalystR@decisionanlayst.com"), person("Decision
Analyst, Inc.", role = "cph"))
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
unit characteristics variables.
(C) 2011 Decision Analyst, Inc. (ChoiceModelR is a trademark
of Decision Analyst, Inc.)

(C) 2012 Decision Analyst, Inc. (ChoiceModelR is a trademark
of Decision Analyst, Inc.)

Ryan Sermas, assisted by John V. Colias, Ph.D.
<DecisionAnalystR@decisionanalyst.com>
c(person("Ryan", "Sermas", role = "aut", email =
"DecisionAnalystR@decisionanalyst.com"), person(c("John","V"),
"Colias", role = c("ctb","cre"), email =
"jcolias@decisionanalyst.com"), person("Decision Analyst,
Inc.", role = "cph"))

c(person("Ryan", "Sermas", role = "aut", email = "DecisionAnalystR@decisionanalyst.com"), person(c("John","V"), "Colias", role = c("ctb","cre"), email = "jcolias@decisionanalyst.com"), person("Decision Analyst, Inc.", role = "cph"))
bayesm, MASS, lattice, Matrix, testthat (>= 3.0.0)
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 unit characteristics variables.
Copyright (C) 2012 Decision Analyst, Inc.; 604 Avenue H
East, Arlington, Texas 76011; www.decisionanalyst.com;
817-640-6166 (ChoiceModelR is a trademark of Decision Analyst,
Inc.)
Ryan Sermas [aut],
John V Colias [ctb, cre],
Decision Analyst, Inc. [cph]