Xiaobei's miscellaneous classes and functions
This is Xiaobei's miscellaneous classes and functions useful when
developing R packages, particularly for OOP using R Reference Class.
'Xmisc-package.R' 'util.R' 'list.R' 'internal.R' 'generic.R'
'xrefclass.R' 'valueparser.R' 'argumentparser.R' 'logging.R'
c(
person("Xiaobei", "Zhao", email="xiaobei@binf.ku.dk",
role=c("aut", "cre", "cph"))
)

This is Xiaobei's miscellaneous classes and functions useful when developing R packages, particularly for OOP using R Reference Class.

'Xmisc-package.R' 'imports.R' 'util.R' 'list.R' 'internal.R'
'generic.R' 'xrefclass.R' 'valueparser.R' 'argumentparser.R'
'logging.R' 'unittest.R'

Monica Bécue-Bertaut, Ramón Alvarez-Esteban, Josep-Anton Sánchez-
Espigares
A complete set of functions devoted to statistical analysis of
documents.
tm, stringr, slam, stats, graphics, gridExtra, utils

Monica Bécue-Bertaut, Ramón Alvarez-Esteban, Josep-Anton Sánchez-Espigares
Provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to 'FactoMineR' functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. CaGalt() helps to explore the relationships between lexical choices and contextual variables. See <http://www.Xplortext.org> for examples.

Mónica Bécue-Bertaut, Ramón Alvarez-Esteban, Josep-Anton Sánchez-Espigares
Provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to 'FactoMineR' functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. See <http://www.xplortext.org> for examples.
ggdendro, graphics, gridExtra, MASS, methods, stringi,
stringr, slam, stats, utils, flexclust, flashClust