dataR2C: Transform a (normal) data frame to be compatible with...
In ClustMMDD: Variable Selection in Clustering by Mixture Models for Discrete Data

Description Usage Arguments Value Author(s) See Also Examples

dataR2C(x, ploidy) returns a list.

1	dataR2C(x, ploidy = 1)

`x`	A data frame or a matrix with the number of columns equal to number(variables)ploidy*.
`ploidy`	The number of unordered observations represented by a string in `xdata`. For example, for genotypic data from diploid individual, ploidy = 2 : two columns for one variable.

A list of elements needed for ClustMMDD main functions :

data : A matrix compatible with ClustMMDD main functions.
ploidy : The number of columns for each variable. It is the ploidy for genotypic data
N : The number of lines in x.
P : The number of categorical variables describing the dataset : P = ncol(x)/ploidy.
N_LEVELS : The vector of the numbers of levels for the variables.
LEVELS : The levels for the variables.
COUNT : The observed counts of the levels.
FREQ : The observed frequencies.

Wilson Toussile

cutEachCol in ClustMMDD package.

data(genotype1)
head(genotype1)
genotype2 = cutEachCol(genotype1[, -11], 2)
head(genotype2)
genotype3 = dataR2C(genotype2, ploidy = 2)
head (genotype3$data)
str(genotype3)