Package edu.cmu.tetrad.regression

Class LogisticRegression.Result

java.lang.Object

edu.cmu.tetrad.regression.LogisticRegression.Result

All Implemented Interfaces:

TetradSerializable, Serializable

Enclosing class:

LogisticRegression

public static class LogisticRegression.Result
extends Object
implements TetradSerializable

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
Result(String target, List<String> regressorNames, double[] xMeans, double[] xStdDevs, int numRegressors, int ny0, int ny1, double[] coefs, double[] stdErrs, double[] probs, double intercept, double logLikelihood, double chiSq, double alpha)	Constructs a new LinRegrResult.

Method Summary

Modifier and Type	Method	Description
double[]	getCoefs()	The array of regression coefficients.
double	getIntercept()
double	getLogLikelihood()	The log likelihood of the regression
int	getNumRegressors()	The number of regressors.
int	getNy0()	The number of data points with target = 0.
int	getNy1()	The number of data points with target = 1.
double[]	getProbs()	The array of coefP-values for the regression coefficients.
List<String>	getRegressorNames()	The variables.
double[]	getStdErrs()	The array of standard errors for the regression coefficients.
String	getTarget()	The target.
double[]	getxMeans()	THe array of means.
double[]	getxStdDevs()	The array of standard devs.
static LogisticRegression.Result	serializableInstance()	Generates a simple exemplar of this class to test serialization.
String	toString()

Methods inherited from class java.lang.Object

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

Constructor Details

Result

public Result(String target,
 List<String> regressorNames,
 double[] xMeans,
 double[] xStdDevs,
 int numRegressors,
 int ny0,
 int ny1,
 double[] coefs,
 double[] stdErrs,
 double[] probs,
 double intercept,
 double logLikelihood,
 double chiSq,
 double alpha)

Constructs a new LinRegrResult.

Parameters:

numRegressors - the number of regressors

ny0 - the number of cases with target = 0.

ny1 - the number of cases with target = 1.

coefs - the array of regression coefficients.

stdErrs - the array of std errors of the coefficients.

probs - the array of P-values for the regression

Method Details

serializableInstance

public static LogisticRegression.Result serializableInstance()

Generates a simple exemplar of this class to test serialization.

getRegressorNames

public List<String> getRegressorNames()

The variables.

getTarget

public String getTarget()

The target.

getNy0

public int getNy0()

The number of data points with target = 0.

getNy1

public int getNy1()

The number of data points with target = 1.

getNumRegressors

public int getNumRegressors()

The number of regressors.

getCoefs

public double[] getCoefs()

The array of regression coefficients.

getStdErrs

public double[] getStdErrs()

The array of standard errors for the regression coefficients.

getProbs

public double[] getProbs()

The array of coefP-values for the regression coefficients.

getxMeans

public double[] getxMeans()

THe array of means.

getxStdDevs

public double[] getxStdDevs()

The array of standard devs.

getIntercept

public double getIntercept()

getLogLikelihood

public double getLogLikelihood()

The log likelihood of the regression

toString

public String toString()

Overrides:

toString in class Object