Package edu.cmu.tetrad.regression

Class RegressionResult

java.lang.Object

edu.cmu.tetrad.regression.RegressionResult

All Implemented Interfaces:

TetradSerializable, Serializable

public class RegressionResult
extends Object
implements TetradSerializable

Stores the various components of a regression result so they can be passed around together more easily.

Author:

josephramsey

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
RegressionResult(boolean zeroInterceptAssumed, String[] regressorNames, int n, double[] b, double[] t, double[] p, double[] se, double r2, double rss, double alpha, Vector res)	A result for a variety of regression algorithm.

Method Summary

Modifier and Type	Method	Description
double[]	getCoef()
int	getN()
int	getNumRegressors()
double[]	getP()
String	getPreamble()
double	getPredictedValue(double[] x)
String[]	getRegressorNames()
Vector	getResiduals()
TextTable	getResultsTable()
double[]	getSe()
double[]	getT()
static RegressionResult	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

RegressionResult

public RegressionResult(boolean zeroInterceptAssumed,
 String[] regressorNames,
 int n,
 double[] b,
 double[] t,
 double[] p,
 double[] se,
 double r2,
 double rss,
 double alpha,
 Vector res)

A result for a variety of regression algorithm.

Parameters:

zeroInterceptAssumed - True iff a zero intercept was assumed in doing the regression, in which case this coefficient is provided; otherwise, not.

regressorNames - The list of regressor variable names, in order.

n - The sample size.

b - The list of coefficients, in order. If a zero intercept was not assumed, this list begins with the intercept.

t - The list of t-statistics for the coefficients, in order. If a zero intercept was not assumed, this list begins with the t statistic for the intercept.

p - The p-values for the coefficients, in order. If a zero intercept was not assumed, this list begins with the p value for the intercept.

se - The standard errors for the coefficients, in order. If a zero intercept was not assumed, this list begins with the standard error of the intercept.

r2 - The R squared statistic for the regression.

rss - The residual sum of squares of the regression.

alpha - The alpha value for the regression, determining which regressors are taken to be

Method Details

serializableInstance

public static RegressionResult serializableInstance()

Generates a simple exemplar of this class to test serialization.

getN

public int getN()

Returns:

the number of data points.

getNumRegressors

public int getNumRegressors()

Returns:

the number of regressors.

getCoef

public double[] getCoef()

Returns:

the array of regression coeffients.

getT

public double[] getT()

Returns:

the array of t-statistics for the regression coefficients.

getP

public double[] getP()

Returns:

the array of p-values for the regression coefficients.

getSe

public double[] getSe()

getRegressorNames

public String[] getRegressorNames()

getPredictedValue

public double getPredictedValue(double[] x)

toString

public String toString()

Overrides:

toString in class Object

getResultsTable

public TextTable getResultsTable()

getPreamble

public String getPreamble()

getResiduals

public Vector getResiduals()