tca: Taxicab Correspondance analysis

In TaxicabCA: Taxicab Correspondence Analysis

Description

Computes the Taxicab correspondance analysis of a matrix of non-negative numbers

Usage

tca(
  Y,
  nAxes = 2,
  dataName = NULL,
  combineCollinearRows = c(F, T),
  combineCollinearCols = c(F, T),
  algorithm = c("exhaustive", "criss-cross", "genetic"),
  returnInputMatrix = c(T, F),
  verbose = (nAxes > 2),
  exhaustiveAlgorithmMaxnCol = 20,
  L1MaxDeltaMax = 10^-10
)

Arguments

Y	A m x n matrix of non-negative numbers. If Y is not a matrix, the 'as.matrix' transformation will be attempted. Missing values are not allowed.
nAxes	Number of axes to compute
dataName	A name to be used to identify the outputs in 'plot' and 'saveTCA' ()
combineCollinearRows	Should collinear rows be combined?
combineCollinearCols	Should collinear columns be combined?
algorithm	Algorthim requested - may be abreviated to first two letters
returnInputMatrix	Will the input matrix be returned
verbose	Report progress (default) or not
exhaustiveAlgorithmMaxnCol	Maximum size for exhaustive search
L1MaxDeltaMax	Change of L1 norm acceptable for convergence in iterative searches

Details

Computations are carried out on the transposed matrix if nrow(Y) < ncol(Y). In the following, we assume that nrow(Y) >= ncol(Y)

Row and column names will be created if necessary.

Zeros rows and columns are removed.

If ncol(Y) <= exhaustiveAlgorithmMaxnCol the exhaustive algorithm used unless otherwise specified.

If ncol(Y) > exhaustiveAlgorithmMaxnCol the genetic algorithm used unless otherwise specified.

Algorithm = exhaustive is overridden if ncol(Y) > exhaustiveAlgorithmMaxnCol.

For ncol(Y) <= exhaustiveAlgorithmMaxnCol, the user may want to specify algorithm = genetic is nrow(Y) is very large, since exhaustive computation may be slow.

If ncol(Y) <= exhaustiveAlgorithmMaxnCol the genetic algorithm is used unless otherwise specified.

(ncol(Y) = 20 appears to be the maximum practical on 2017 vintage Intel-based desktops).

Value

A list with class 'tca' containing the following components:

dispersion	A nAxes-length vector of matrix of column contributions
rowScores	A m x nAxes matrix of column contributions
colScores	A nAxes x n matrix of row contributions
rowMass	Row weights: apply(Y,1,sum)/sum(Y)
colMass	Column weights: apply(Y,2,sum)/sum(Y)
dataName	A name to be used to identify the output in 'plot' and 'save'
algorithm	Algorithm used (may be different from the algorythm requested)
dataMatrixTotal	Sum of the input matrix entries
dataMatrix	The matrix used in the computation
rowColCombined	A list describing removed or combined rows and columns, if any

Examples

tca(rodent,nAxes=4)
tca(rodent,nAxes=4,combineCollinearRows=c(TRUE,FALSE))

TaxicabCA documentation built on Dec. 11, 2019, 5:07 p.m.