ComputeLambda

Computation and visualization of Taxicab Correspondence Analysis, Choulakian (2006) <doi:10.1007/s11336-004-1231-4>. Classical correspondence analysis (CA) is a statistical method to analyse 2-dimensional tables of positive numbers and is typically applied to contingency tables (Benzecri, J.-P. (1973). L'Analyse des Donnees. Volume II. L'Analyse des Correspondances. Paris, France: Dunod). Classical CA is based on the Euclidean distance. Taxicab CA is like classical CA but is based on the Taxicab or Manhattan distance. For some tables, Taxicab CA gives more informative results than classical CA.

Jacques Allard

TaxicabCA

Taxicab Correspondence Analysis

Vartan Choulakian

ComputeLambda function

<dl><dt>uFT</dt>
<dd>A vector of 0s and 1s of lenght nc: (-1)^uFT is a unit vector in Linf norm</dd>
<dt>pResidual</dt>
<dd>A matrix with nc columns</dd></dl>

Arguments

L1 norm of a projection — ComputeLambda

<dl>

<dt>uFT</dt>
<dd>A vector of 0s and 1s of lenght nc: (-1)^uFT is a unit vector in Linf norm</dd>


<dt>pResidual</dt>
<dd>A matrix with nc columns</dd>

</dl>

ComputeLambda: L1 norm of a projection

Description

Usage

Value

Arguments

Details

Examples