com.pervasive.datarush.analytics.regression

Class AbstractPMMLRegressionModel.NumericPredictor

java.lang.Object

com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel.NumericPredictor

Enclosing class:

AbstractPMMLRegressionModel

public static final class AbstractPMMLRegressionModel.NumericPredictor
extends Object

Capture information about numeric predictor values.

Constructor Summary

Constructors

Constructor and Description
AbstractPMMLRegressionModel.NumericPredictor(String fieldName, double coefficient) Create a numeric predictor for the given independent variable with the default exponent value of 1.
AbstractPMMLRegressionModel.NumericPredictor(String fieldName, double coefficient, int degreesOfFreedom, double standardError, double tTest, double pValue) Create a numeric predictor for the given independent variable with the default exponent value of 1 and the specified statistics.
AbstractPMMLRegressionModel.NumericPredictor(String fieldName, int exponent, double coefficient) Create a numeric predictor for the given independent variable.
AbstractPMMLRegressionModel.NumericPredictor(String fieldName, int exponent, double coefficient, int degreesOfFreedom, double standardError, double tTest, double pValue) Create a numeric predictor for the given independent variable with the specified statistics.

Method Summary

Methods

Modifier and Type	Method and Description
double	calculate(double value) Given a value of the independent variable, calculate its value to add to the resultant dependent value.
double	getCoefficient() Get the coefficient value.
Integer	getDegreesOfFreedom() Get the degrees of freedom value.
int	getExponent() Get the exponent value.
String	getFieldName() Get the independent variable name.
Double	getPValue() Get the p value.
Double	getStandardError() Get the standard error value.
Double	getTTest() Get the t-test value.
void	setExtensionStatistic(String name, double value)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

AbstractPMMLRegressionModel.NumericPredictor

public AbstractPMMLRegressionModel.NumericPredictor(String fieldName,
                                            int exponent,
                                            double coefficient)

Create a numeric predictor for the given independent variable.

Parameters:

fieldName - name of the independent variable

exponent - exponent of this variable

coefficient - coefficient (Beta) of this variable

AbstractPMMLRegressionModel.NumericPredictor

public AbstractPMMLRegressionModel.NumericPredictor(String fieldName,
                                            int exponent,
                                            double coefficient,
                                            int degreesOfFreedom,
                                            double standardError,
                                            double tTest,
                                            double pValue)

Create a numeric predictor for the given independent variable with the specified statistics.

Parameters:

fieldName - name of the independent variable

exponent - exponent of this variable

coefficient - coefficient (Beta) of this variable

degreesOfFreedom -

standardError -

tTest -

pValue -

AbstractPMMLRegressionModel.NumericPredictor

public AbstractPMMLRegressionModel.NumericPredictor(String fieldName,
                                            double coefficient)

Create a numeric predictor for the given independent variable with the default exponent value of 1.

Parameters:

fieldName - name of the independent variable

coefficient - coefficient (Beta) of this variable

AbstractPMMLRegressionModel.NumericPredictor

public AbstractPMMLRegressionModel.NumericPredictor(String fieldName,
                                            double coefficient,
                                            int degreesOfFreedom,
                                            double standardError,
                                            double tTest,
                                            double pValue)

Create a numeric predictor for the given independent variable with the default exponent value of 1 and the specified statistics.

Parameters:

fieldName - name of the independent variable

coefficient - coefficient (Beta) of this variable

degreesOfFreedom -

standardError -

tTest -

pValue -

Method Detail

getFieldName

public String getFieldName()

Get the independent variable name.

Returns:

independent variable name

getExponent

public int getExponent()

Get the exponent value.

Returns:

exponent value

getCoefficient

public double getCoefficient()

Get the coefficient value.

Returns:

coefficient value

getDegreesOfFreedom

public Integer getDegreesOfFreedom()

Get the degrees of freedom value.

Returns:

degrees of freedom value

getStandardError

public Double getStandardError()

Get the standard error value.

Returns:

standard error value

getTTest

public Double getTTest()

Get the t-test value.

Returns:

t-test value

getPValue

public Double getPValue()

Get the p value.

Returns:

p value

calculate

public double calculate(double value)

Given a value of the independent variable, calculate its value to add to the resultant dependent value.

Parameters:

value - independent variable value

Returns:

contribution to dependent variable

setExtensionStatistic

public void setExtensionStatistic(String name,
                         double value)