A genetic algorithm approach to determine stratum boundaries and
sample sizes of each stratum in stratified sampling
Sebnem Er, Timur Keskinturk, Charlie Daly
This is a Genetic Algorithm package for the determination
of the stratum boundaries and sample sizes of each stratum in
stratified sampling

Framework for Generalized Subspace Pattern Mining
Generalized subspace pattern mining in data arrays, using a genetic algorithm framework.

Genetic Similarity in User-Based Collaborative Filtering
Farimah Houshmand Nanehkaran, Seyed Mohammad Reza Lajevardi <R.Lajevardi@iaukashan.ac.ir>, Mahmoud Mahlouji Bidgholi <m.mahlouji@iaukashan.ac.ir>
The genetic algorithm can be used directly to find the similarity of users and more effectively to increase the efficiency of the collaborative filtering method.
By identifying the nearest neighbors to the active user, before the genetic algorithm, and by identifying suitable starting points, an effective method for user-based collaborative filtering method has been developed.
This package uses an optimization algorithm (continuous genetic algorithm) to directly find the optimal similarities between active users (users for whom current recommendations are made) and others.
First, by determining the nearest neighbor and their number, the number of genes in a chromosome is determined. Each gene represents the neighbor's similarity to the active user.
By estimating the starting points of the genetic algorithm, it quickly converges to the optimal solutions.
The positive point is the independence of the genetic algorithm on the number of data that for big data is an effective help in solving the problem.

General ANOVA Design (GAD): Analysis of variance from general
principles
Leonardo Sandrini-Neto & Mauricio G. Camargo
R (>= 2.7.0), stats, matrixStats, R.methodsS3
This package analyses complex ANOVA models with any
combination of orthogonal/nested and fixed/random factors, as
described by Underwood (1997). There are two restrictions: (i)
data must be balanced; (ii) fixed nested factors are not
allowed. Homogeneity of variances is checked using Cochran's C
test and "a posteriori" comparisons of means are done using
Student-Newman-Keuls (SNK) procedure.