knitr, testthat, rmarkdown, pmml (<= 1.5.7)

Create and Maintain a Relational Database of Data from
PubMed/MEDLINE
c(person('Jake', 'Hughey', , 'jakejhughey@gmail.com', c('aut', 'cre')),
person('Josh', 'Schoenbachler', , 'josh.schoenbachler@gmail.com', 'aut'),
person('Elliot', 'Outland', , 'ehoutland@gmail.com', 'aut'))
Provides a simple interface for extracting various elements from
the publicly available PubMed XML files, incorporating PubMed's regular
updates, and combining the data with the NIH Open Citation Collection. See
Schoenbachler and Hughey (2021) <doi:10.7717/peerj.11071>.
bigrquery (>= 1.3.2), doParallel (>= 1.0.16), RMariaDB (>=
1.0.9), RPostgres (>= 1.2.0), RSQLite (>= 2.2.0), testthat (>=
2.3.2), knitr, rmarkdown
Jake Hughey [aut, cre],
Josh Schoenbachler [aut],
Elliot Outland [aut]

person("Michal", "Oleszak", email = "oleszak.michal@gmail.com", role = c("aut", "cre"))
Dynamic panel modelling framework based on an empirical-Bayes approach.
Contains tools for computing point forecasts and bootstrapping prediction intervals.
Reference: Liu et al. (2016) <doi:10.2139/ssrn.2889000>.
plm, pracma, MASS, Matrix, minqa, dplyr, data.table, moments,
magrittr, ggplot2, stats, utils, graphics

Fitting probability models for ranking data. Current, only
complete rankings are supported by this package.

Fitting probability models for ranking data. Current, only complete rankings are supported by this package.

Fitting probability models for ranking data. Currently,
only complete rankings are supported by this package.

Descriptive statistics (mean rank, pairwise frequencies,
and marginal matrix), Analytic Hierarchy Process models (with
Saaty's and Koczkodaj's inconsistencies), probability models
(Luce models, distance-based models, and rank-ordered logit
models) and visualization with multidimensional preference
analysis for ranking data are provided. Current, only complete
rankings are supported by this package.

Descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce models, distance-based models, and rank-ordered logit models) and visualization with multidimensional preference analysis for ranking data are provided. Current, only complete rankings are supported by this package.