Class GeneralisedOrderedRegression<E1 extends Enum<E1> & IntegerValuedEnum>
java.lang.Object
microsim.statistics.regression.GeneralisedOrderedRegression<E1>
- Type Parameters:
E1- event type.
- All Implemented Interfaces:
IDiscreteChoiceModel<E1>
public class GeneralisedOrderedRegression<E1 extends Enum<E1> & IntegerValuedEnum>
extends Object
implements IDiscreteChoiceModel<E1>
Generalised Ordered Discrete Variable Models
- Author:
- Justin van de Ven 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 higher values of i reflect some natural ordering of the set Define yhat_j = sum(y_j+1,...,y_n) yhatstar_j = Xb_j - e_j yhat_j = 1 if yhatstar_j>=0 and 0 otherwise P(yhat_j=1|X) = P(yhatstar_j>=0|X) = P(Xb_j-e_j>=0) = F(Xb_j)
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Constructor Summary
ConstructorsConstructorDescriptionGeneralisedOrderedRegression(RegressionType type, Class<E1> enumType, MultiKeyCoefficientMap multinomialCoefficients) -
Method Summary
Modifier and TypeMethodDescriptiongetProbabilities(IDoubleSource iDblSrc, Class<E2> Regressors) <E2 extends Enum<E2>>
doublegetProbability(E1 event, IDoubleSource iDblSrc, Class<E2> Regressors)
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Constructor Details
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GeneralisedOrderedRegression
public GeneralisedOrderedRegression(RegressionType type, Class<E1> enumType, MultiKeyCoefficientMap multinomialCoefficients)
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Method Details
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getEventList
- Specified by:
getEventListin interfaceIDiscreteChoiceModel<E1 extends Enum<E1> & IntegerValuedEnum>
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getProbability
public <E2 extends Enum<E2>> double getProbability(E1 event, IDoubleSource iDblSrc, Class<E2> Regressors) - Specified by:
getProbabilityin interfaceIDiscreteChoiceModel<E1 extends Enum<E1> & IntegerValuedEnum>
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getProbabilities
public <E2 extends Enum<E2>> Map<E1,Double> getProbabilities(IDoubleSource iDblSrc, Class<E2> Regressors) - Specified by:
getProbabilitiesin interfaceIDiscreteChoiceModel<E1 extends Enum<E1> & IntegerValuedEnum>
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