Title: Nonparametric Methods for Directional Data
Authors@R: person(given = "Eduardo", family = "García-Portugués",
role = c("aut", "cre"), email = "edgarcia@est-econ.uc3m.es")
Description: Nonparametric kernel density estimation, bandwidth selection,
and other utilities for analyzing directional data. Implements the estimator
cross-validation bandwidth selectors in Hall, Watson and Cabrera (1987)
<doi:10.1093/biomet/74.4.751> and the plug-in bandwidth selectors in
Author: Eduardo García-Portugués [aut, cre]

role = c("aut", "cre"), email = "edgarcia@est-econ.uc3m.es",

Title: Linear Regressions with a Latent Outcome Variable
person("Paul", "Bailey", role=c("aut", "cre"), email="pbailey@air.org"),
Imports: minqa, foreach, iterators, methods, Matrix, haven, Rcpp
Description: Fit linear models, estimating score distributions for groups of people, following Cohen and Jiang (1999) <doi:10.2307/2669917>. In this model, the response is a latent trait (such as student ability) and raw item responses are combined with item difficulties in an item response theory (IRT) framework to form a density for each unit (student). This latent trait is then integrated out. This software is intended to fit the same models as the existing software 'AM' <http://am.air.org/>.
Suggests: knitr, rmarkdown, testthat, withr, doParallel, EdSurvey
Note: This publication was prepared for NCES under Contract No.
ED-IES-12-D-0002 with the American Institutes for Research.
Mention of trade names, commercial products, or organizations
does not imply endorsement by the U.S. Government.

person("Emmanuel", "Sikali", role="pdr", email = "Emmanuel.Sikali@ed.gov"))

Authors@R: c(person("Emmanuel", "Sikali", role="pdr", email = "Emmanuel.Sikali@ed.gov"),
Imports: foreach, iterators, methods, Matrix, haven, Rcpp, MASS
Description: Fit latent variable linear models, estimating score distributions for groups of people, following Cohen and Jiang (1999) <doi:10.2307/2669917>. In this model, a latent distribution is conditional on students item response, item characteristics, and conditioning variables the user includes. This latent trait is then integrated out. This software is intended to fit the same models as the existing software 'AM' <https://am.air.org/>. As of version 2, also allows the user to draw plausible values.
Suggests: knitr, rmarkdown, testthat, withr, doParallel, parallel,
ED-IES-12-D-0002/0004 with the American Institutes for
Research. Mention of trade names, commercial products, or
organizations does not imply endorsement by the U.S.