Burg and P.J.F. Groenen (2018) <https://www.jmlr.org/papers/v17/14-526.html>.

Title: An Imperative Library for Data Manipulation
Authors@R: person("Zach", "Flynn", email = "zlflynn@gmail.com", role = c("aut", "cre"))
Description: Implements tools for manipulating data sets and performing regressions in a way that is familiar to users of a popular, but proprietary, statistical package commonly used in the social sciences. Loads a single dataset into memory and implements a set of imperative commands to modify that data and perform regressions and other analysis on the dataset. Offers an alternative to standard R's function-based approach to data manipulation.
Imports: Formula, foreign, readstata13, sandwich, plm, clubSandwich

Imports: Formula, foreign, readstata13, sandwich, plm, clubSandwich,

Title: Draw and Annotate Maps, Especially Charts of the North Atlantic
Author: Hoskuldur Bjornsson, Sigurdur Thor Jonsson, Arni Magnusson, and Bjarki
Maintainer: Sigurdur Thor Jonsson <sigurdur@hafro.is>
Imports: splines, methods, utils, grDevices, graphics, stats
Description: Used by Hafro staff to draw maps showing the distribution of
fishing intensity and catches, and of survey data for Icelandic fish stocks.

Title: Analysis of geostatistical data using Bayes and Empirical Bayes
Description: This package provides functions to fit geostatistical
data. The data can be continuous, binary or count data and the
models implemented are flexible. Conjugate priors are assumed
on some parameters while non-conjugate parameters can be
estimated either by Monte-Carlo or empirical Bayes methods.
Author: Evangelos Evangelou <e.evangelou@maths.bath.ac.uk>, Vivekanda Roy

Title: Analysis of geostatistical data using Bayes and empirical Bayes
on some parameters while inference on the other parameters can
be done through a full Bayesian analysis of by empirical Bayes
Author: Evangelos Evangelou <e.evangelou@maths.bath.ac.uk>, Vivekananda Roy

Title: Analysis of Geostatistical Data using Bayes and Empirical Bayes
Description: Functions to fit geostatistical data. The data can be
continuous, binary or count data and the models implemented are
flexible. Conjugate priors are assumed on some parameters while
inference on the other parameters can be done through a full
Bayesian analysis of by empirical Bayes methods.
Author: Evangelos Evangelou <e.evangelou@maths.bath.ac.uk>, Vivekananda