Class MultinomialRegression<E1 extends Enum<E1> & IntegerValuedEnum>

java.lang.Object
microsim.statistics.regression.MultinomialRegression<E1>
Type Parameters:
E1 - event type.
All Implemented Interfaces:
IDiscreteChoiceModel

public class MultinomialRegression<E1 extends Enum<E1> & IntegerValuedEnum> extends Object implements IDiscreteChoiceModel
Multinomial Discrete Variable Models
Author:
Justin van de Ven NOTE: Probit variant not currently supported Let y define a discrete valued set {y_0,y_1,..., y_n} Each y_i is an indicator variable for discrete value i, where the index i signifies nothing Define P(y_i=1|X) = exp(Xb_i) / sum(exp(Xb_1),...exp(Xb_n)) for all i Identification is permitted by normalising one category, k, such that exp(Xb_k) = 1.0