tepDICA.inference.battery: Discriminant Correspondence Analysis Inference Battery

In TInPosition: Inference Tests for TExPosition

Description

Discriminant Correspondence Analysis (DICA) Inference Battery via TInPosition

Usage

tepDICA.inference.battery(DATA, make_data_nominal = FALSE, DESIGN = NULL, 
	make_design_nominal = TRUE,	
	group.masses = NULL, weights = NULL, 
 	symmetric = TRUE, graphs = TRUE, k = 0,
	test.iters = 100, critical.value = 2)

Arguments

DATA	original data to perform a DICA on. Data can be contingency (like CA) or categorical (like MCA).
make_data_nominal	a boolean. If TRUE (default), DATA is recoded as a dummy-coded matrix. If FALSE, DATA is a dummy-coded matrix.
DESIGN	a design matrix to indicate if rows belong to groups. Required for DICA.
make_design_nominal	a boolean. If TRUE (default), DESIGN is a vector that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a dummy-coded matrix.
group.masses	a diagonal matrix or column-vector of masses for the groups.
weights	a diagonal matrix or column-vector of weights for the column it
symmetric	a boolean. If TRUE (default) symmetric factor scores for rows.
graphs	a boolean. If TRUE (default), graphs and plots are provided (via epGraphs)
k	number of components to return.
test.iters	number of iterations
critical.value	numeric. A value, analogous to a z- or t-score to be used to determine significance (via bootstrap ratio).

Details

tepDICA.inference.battery performs discriminant correspondence analysis and inference tests on based on data and (row) design matrices.

If the expected time to compute the results (based on test.iters) exceeds 1 minute, you will be asked (via command line) if you want to continue.

Value

Returns two lists ($Fixed.Data and $Inference.Data). For $Fixed.Data, see tepDICA and coreCA for details on the descriptive (fixed-effects) results.

$Inference.Data returns:

omni	Permutation tests of components. p-values ($p.val) and distributions of total inertia ($inertia.perm)
r2	Permutation tests of R-squared value. p-values ($p.val) and distributions of R2s ($r2.perm)
components	Permutation tests of components. p-values ($p.vals) and distributions of eigenvalues ($eigs.perm) for each component
boot.data	Bootstrap tests for $fi and $fj. Contains distributions. See also boot.ratio.test output details.
loo.data	Leave one out cross-validation tests. Includes assignments ($loo.assign), factor scores ($loo.fii), LOO and fixed confusion matrices ($loo.confuse, $fixed.confuse), and accuracy ($loo.acc, $fixed.acc)

Author(s)

Derek Beaton, Jenny Rieck, Hervé Abdi

Examples

	data(dica.wine)
	data<-dica.wine$data
	design<-dica.wine$design
	dica.res <- 
		tepDICA.inference.battery(data,DESIGN=design,
		make_design_nominal=FALSE,test.iters=50)

Example output

Loading required package: prettyGraphs
Loading required package: TExPosition
Loading required package: ExPosition
Loading required package: InPosition
[1] "It is estimated that your iterations will take 0.01 minutes."
[1] "R is not in interactive() mode. Resample-based tests will be conducted. Please take note of the progress bar."
================================================================================dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
dev.new(): using pdf(file="Rplots5.pdf")
dev.new(): using pdf(file="Rplots6.pdf")

TInPosition documentation built on May 2, 2019, 3:46 p.m.