ircNorm: Function for iterated row and column normalization of valued...

In blockmodelingTest: Testing Version: Generalized and Classical Blockmodeling of Valued Networks

Description

The aim is to obtain a matrix with row and column sums equal to 1. This is achieved by iterating row and column normalization. This is usually not possible if any row or column has only 1 non-zero cell.

Usage

ircNorm(M, eps = 10^-12, maxiter = 1000)

Arguments

M	A non-negative valued matrix to be normalized.
eps	The maximum allows squared deviation of a row or column's maximum from 1 (if not exactly 0). Also, if the all deviations in two consequtive iterations are smaller, the process is terminated.
maxiter	Maximum number of iterations. If reached, the process is terminated and the current solution returned.

Value

Normalized matrix.

Author(s)

Aleš Žiberna

Examples

A <- matrix(runif(100), ncol = 10)
A # A non-normalized matrix with different row and column sums.
apply(A, 1, sum)
apply(A, 2, sum)
A.norm <- ircNorm(A)
A.norm # Normalized matrix with all row and column sums approximately 1.
apply(A.norm, 1, sum)
apply(A.norm, 2, sum)

blockmodelingTest documentation built on May 2, 2019, 5:57 p.m.