Package edu.cmu.tetrad.regression

Class RegressionCovariance

java.lang.Object
edu.cmu.tetrad.regression.RegressionCovariance
All Implemented Interfaces:
Regression
public class RegressionCovariance extends Object implements Regression
Implements a regression model from correlations--that is, from a correlation matrix, a list of standard deviations, and a list of means.
Version:
$Id: $Id
Author:
josephramsey

  • Constructor Summary

    Constructors
    Constructor
    Description
    RegressionCovariance(ICovarianceMatrix covariances)
    Constructs a covariance-based regression model using the given covariance matrix, assuming that no means are specified.

  • Method Summary

    Modifier and Type
    Method
    Description
    Graph
    getGraph()
    Getter for the field graph.
    RegressionResult
    regress(Node target, Node... regressors)
    regress.
    RegressionResult
    regress(Node target, List<Node> regressors)
    Regresses the given target on the given regressors, yielding a regression plane, in which coefficients are given for each regressor plus the constant (if means have been specified, that is, for the last), and se, t, and p values are given for each regressor.
    void
    setAlpha(double alpha)
    Sets the significance level at which coefficients are judged to be significant.

    Methods inherited from class java.lang.Object

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

  • Constructor Details

    • RegressionCovariance

      public RegressionCovariance(ICovarianceMatrix covariances)
      Constructs a covariance-based regression model using the given covariance matrix, assuming that no means are specified.
      Parameters:
      covariances - The covariance matrix.

  • Method Details

    • setAlpha

      public void setAlpha(double alpha)
      Sets the significance level at which coefficients are judged to be significant.

      Sets the cutoff for significance. Parameters with p values less than this will be labeled as significant.

      Specified by:
      setAlpha in interface Regression
      Parameters:
      alpha - the significance level.

    • getGraph

      public Graph getGraph()

      Getter for the field graph.

      Specified by:
      getGraph in interface Regression
      Returns:
      This graph.

    • regress

      public RegressionResult regress(Node target, List<Node> regressors)
      Regresses the given target on the given regressors, yielding a regression plane, in which coefficients are given for each regressor plus the constant (if means have been specified, that is, for the last), and se, t, and p values are given for each regressor.
      Specified by:
      regress in interface Regression
      Parameters:
      target - The variable being regressed.
      regressors - The list of regressors.
      Returns:
      the regression plane.

    • regress

      public RegressionResult regress(Node target, Node... regressors)

      regress.

      Specified by:
      regress in interface Regression
      Parameters:
      target - a Node object
      regressors - a Node object
      Returns:
      a RegressionResult object