Defines the logistic regression B coefficients. Suppose y takes values in k ordered categories, and let p_ij be the cumulative probability that y(i) falls in the j'th category or higher. Ordinal logistic regression model is defined as: 

logit(p_ij) = theta(j) + A_i'B , i = 1,..,length(Y), j = 1,..,k-1, 

where A_i is the i'th row of A . The number of ordinal categories k is taken to be the number of distinct values of int(y). If k is 2 the model is ordinary logistic regression. 

Set B values to define initial estimates for B coefficients. Setting B values is not mandatory. You can also set AutoInitEstimates to true and force the algorithm to calculate initial estimates for B and Theta. After the Recalc call B stores logistic regression model B coefficient estimates.

AutoInitEstimates, Theta

TMtxLogistReg Properties