Title: Accurate Generalized Linear Model
person("Kenji", "Kondo", role=c("aut", "cre", "cph"), email="kkondo.odnokk@gmail.com"),
Description: Provides functions to fit Accurate Generalized Linear Model (AGLM) models, visualize them, and predict for new data. AGLM is defined as a regularized GLM which applies a sort of feature transformations using a discretization of numerical features and specific coding methodologies of dummy variables. For more information on AGLM, see Suguru Fujita, Toyoto Tanaka, Kenji Kondo and Hirokazu Iwasawa (2020) <https://www.institutdesactuaires.com/global/gene/link.php?doc_id=16273&fg=1>.
Imports: glmnet (>= 4.0.2), assertthat, methods, mathjaxr
Suggests: testthat, knitr, rmarkdown, MASS, faraway

Title: Aggregation Operators and Preordered Sets
Description: Tools supporting multi-criteria decision making, including
variable number of criteria, by means of aggregation operators
and preordered sets. Possible applications include, but are not
limited to, scientometrics and bibliometrics.
Depends: R (>= 2.12.0), base, stats, grDevices, graphics, Matrix,
email = "gagolews@rexamine.com"), person("Anna", "Cena", role =
Author: Marek Gagolewski [aut, cre], Anna Cena [ctb]

Depends: R (>= 2.12.0), stats, grDevices, graphics, Matrix, igraph

Description: Tools supporting multi-criteria and group decision making,
including variable number of criteria, by means of
fuzzy logic connectives, fusion functions,
and preordered sets. Possible applications include,
but are not limited to, quality management, scientometrics,
Depends: R (>= 3.0), stats, grDevices, graphics

Title: Tutorial Analysis of Some Agricultural Experiments
Description: Example software for the analysis of data from designed
experiments, especially agricultural crop experiments. The basics
of the statistical analysis of designed experiments are discussed
using real examples from agricultural field trials.
A range of statistical methods are  exemplified using a range
of R statistical packages. The experimental
data is made available as separate data sets for each example
and the R analysis code is made available as example code.
The example code can be readily extended, as required.
Imports: lmerTest, lsmeans, pbkrtest, lattice, nlme, ggplot2