R: Updating a Burt matrix in Joint Correspondence Analysis

iterate.mjca {ca} | R Documentation

## Updating a Burt matrix in Joint Correspondence Analysis

### Description

Updating a Burt matrix in Joint Correspondence Analysis based on iteratively weighted least squares.

### Usage

    iterate.mjca(B, lev.n, nd = 2, maxit = 50, epsilon = 0.0001)

### Arguments

`B` | A Burt matrix.
`lev.n` | The number of levels for each factor from the original response pattern matrix.
`nd` | The required dimensionality of the solution.
`maxit` | The maximum number of iterations.
`epsilon` | A convergence criterion for the maximum absolute difference of updated values compared to the previous values. The iteration is completed when all differences are smaller than `epsilon`.

### Details

The function `iterate.mjca` computes the updated Burt matrix. This function is called from the function `mjca` when the option `lambda="JCA"`, i.e. when a Joint Correspondence Analysis is performed.

### Value

`B.star` | The updated Burt matrix
`crit` | Vector of length 2 containing the number of iterations and epsilon

### See Also

`mjca`

[Package ca version 0.70 Index]