ircNorm: Function for iterated row and column normalization of valued...
In blockmodelingOld: Generalized and Classical Blockmodeling of Valued Networks

Description Usage Arguments Value Author(s) Examples

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.

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

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

Normalized matrix.

Aleš Žiberna

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 aproximately 1.
apply(A.norm,1,sum)
apply(A.norm,2,sum)