Title: Modelling Multivariate Binary Data with Blocks of Specific
Description: Modelling Multivariate Binary Data with Blocks of Specific One-Factor Distribution. Variables are grouped into independent blocks. Each variable is described by two continuous parameters (its marginal probability and its dependency strength with the other block variables), and one binary parameter (positive or negative dependency). Model selection consists in the estimation of the repartition of the variables into blocks. It is carried out by the maximization of the BIC criterion by a deterministic (faster) algorithm or by a stochastic (more time consuming but optimal) algorithm. Tool functions facilitate the model interpretation.

Title: Stepwise Variable Selection Procedures for Regression Analysis
Author: International-Harvard Statistical Consulting Company <nhsc2010@hotmail.com>
Description: The stepwise variable selection procedure (with iterations
between the 'forward' and 'backward' steps) can be used to obtain
the best candidate final regression model in regression analysis.
All the relevant covariates are put on the 'variable list' to be
selected. The significance levels for entry (SLE) and for stay
(SLS) are usually set to 0.15 (or larger) for being conservative.
Then, with the aid of substantive knowledge, the best candidate
final regression model is identified manually by dropping the
covariates with p value > 0.05 one at a time until all regression
coefficients are significantly different from 0 at the chosen alpha

Title: Chi-Squared Test for Goodness of Fit and Independence Test
person("Atchanut", "Rattanalertnusorn", email = "atchanut_r@rmutt.ac.th", role = c("cre","aut")),
person("Issaraporn", "Thiamsorn", email = "t_issaraporn@rmutt.ac.th", role = "aut"))
Description: The chi-squared test for goodness of fit
Author: Atchanut Rattanalertnusorn [cre, aut],

Title: Interface to Myrrix. Myrrix is a complete, real-time, scalable
clustering and recommender system, evolved from Apache Mahout.
Authors@R: c(person("Jan", "Wijffels", role = c("aut", "cre"), email =
Description: Recommendation engine based on Myrrix. Myrrix is a complete,
real-time, scalable clustering and recommender system, evolved from Apache
Mahout. It uses Alternating Least Squares to build a recommendation engine.
Depends: R (>= 2.6.0), methods, Myrrixjars