Learn R Programming

TInPosition (version 0.13.6.1)

tepBADA.inference.battery: Barycentric Discriminant Analysis Inference Battery

Description

Barycentric Discriminant Analysis (BADA) Inference Battery via TInPosition.

Usage

tepBADA.inference.battery(DATA, scale = TRUE, center = TRUE, DESIGN = NULL, 
	make_design_nominal = TRUE, 
	group.masses = NULL, weights = NULL, 
	graphs = TRUE, k = 0, 
	test.iters = 100, critical.value = 2)

Arguments

DATA

original data to perform a BADA on.

scale

a boolean, vector, or string. See expo.scale for details.

center

a boolean, vector, or string. See expo.scale for details.

DESIGN

a design matrix to indicate if rows belong to groups. Required for BADA.

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 items.

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).

Value

Returns two lists ($Fixed.Data and $Inference.Data). For $Fixed.Data, see tepBADA and corePCA 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)

Details

tepBADA.inference.battery performs barycentric discriminant 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.

Examples

Run this code
# NOT RUN {
	data(bada.wine)
	data<-bada.wine$data
	design <- bada.wine$design
	bada.res <- 
		tepBADA.inference.battery(data,scale=FALSE,DESIGN=design,
			make_design_nominal=FALSE,test.iters=50)
# }

Run the code above in your browser using DataLab