Updating a Burt matrix in Joint Correspondence Analysis
Updating a Burt matrix in Joint Correspondence Analysis based on iteratively weighted least squares.
iterate.mjca(B, lev.n, nd = 2, maxit = 50, epsilon = 0.0001)
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 |
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.
B.star |
The updated Burt matrix |
crit |
Vector of length 2 containing the number of iterations and epsilon |
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.