Prepare data for use with multimix
data_organise(
dframe,
numClusters,
numIter = 1000,
cdep = NULL,
lcdep = NULL,
minpstar = 1e-09
)
a data frame containing the data set you wish to model.
the clusters you wish to fit.
the maximum number of steps to that the EM agorithm will run before terminating.
a list of multivariate normal cells.
a list of location cells.
Minimum denominator for application of Bayes Rule.
An object of class multimixSettings
which is a list
with the following elements:
cdep
--- a list of multivariate normal cells.
clink
--- column numbers of univariate normal variables.
cprods
--- a list over MVN cells containing a matrix of
pair-wise products of columns in the cell, columns
ordered by pair.index
.
cvals
--- a list over MVN cells containing a matrix of columns of variables in the cell
cvals2
--- a list over MVN cells containing a matrix of squared columns of variables in the cell
dframe
--- the data.frame
of variables
discvar
--- logical: the variable is takes values of either TRUE
or FALSE
dlevs
--- for discrete cells: number of levels
dlink
--- column numbers of univariate discrete variables
dvals
--- a list over discrete cells of level indicator matrices
lc
--- logical: is continuous variable belonging to OT cell TRUE
/FALSE
lcdep
--- a list of OT cells
lcdisc
--- column numbers of discrete variables in OT cells
lclink
--- column numbers of continuous variables in OT cells
lcprods
--- a list over OT cells containing a matrix of pair-wise products of continuous columns in the cell, columns ordered by pair.index
lcvals
--- a list over OT cells containing a matrix of continuous columns of variables in the cell
lcvals2
--- a list over OT cells containing a matrix of squared continuous columns of variables in the cell
ld
--- logical: is discrete variable belonging to OT cell TRUE
/FALSE
ldlevs
--- for discrete variables in OT cells: number of levels
ldlink
--- a column numbers of OT discrete variables
ldvals
--- a list over OT cells of level indicator matrices
ldxc
--- a list over OT cells whose members are lists over levels of matrices of the cell continuous variables whose columns are multiplied by the level indicator column
mc
--- logical: is continuous variable not in OT cell TRUE
/FALSE
md
--- logical: is discrete variable not in OT cell TRUE
/FALSE
minpstar
--- minimum denominator for appliction of Bayes' Rule
n
--- number of observations
numIter
--- the maximum number of steps to that the EM agorithm will run before terminating
oc
--- logical: is continuous variable in univariate cell TRUE
/FALSE
olink
--- column numbers of continuous univariate cells
op
--- length(olink)
ovals
--- n
by op
matrix of continuous univariate variables
ovals2
--- n
by op
matrix of squared continuous univariate variables
numClusters
--- the number of clusters in the model.
data(cancer.df)
D = data_organise(cancer.df, numClusters = 2)