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
The result of a logistic regression.
See Also:

  • 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()
    The intercept.
    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()
    Returns a string representation of the regression results.

    Methods inherited from class java.lang.Object

    equals, 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:
      target - the target variable
      regressorNames - the names of the regressors
      xMeans - the array of means
      xStdDevs - the array of standard devs
      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
      intercept - the intercept
      logLikelihood - the log likelihood of the regression
      chiSq - the chi square statistic
      alpha - the alpha level

  • Method Details

    • serializableInstance

      public static LogisticRegression.Result serializableInstance()
      Generates a simple exemplar of this class to test serialization.
      Returns:
      a LogisticRegression.Result object

    • getRegressorNames

      public List<String> getRegressorNames()
      The variables.
      Returns:
      a List object

    • getTarget

      public String getTarget()
      The target.
      Returns:
      a String object

    • getNy0

      public int getNy0()
      The number of data points with target = 0.
      Returns:
      a int

    • getNy1

      public int getNy1()
      The number of data points with target = 1.
      Returns:
      a int

    • getNumRegressors

      public int getNumRegressors()
      The number of regressors.
      Returns:
      a int

    • getCoefs

      public double[] getCoefs()
      The array of regression coefficients.
      Returns:
      an array of double

    • getStdErrs

      public double[] getStdErrs()
      The array of standard errors for the regression coefficients.
      Returns:
      an array of double

    • getProbs

      public double[] getProbs()
      The array of coefP-values for the regression coefficients.
      Returns:
      an array of double

    • getxMeans

      public double[] getxMeans()
      THe array of means.
      Returns:
      an array of double

    • getxStdDevs

      public double[] getxStdDevs()
      The array of standard devs.
      Returns:
      an array of double

    • getIntercept

      public double getIntercept()
      The intercept.
      Returns:
      a double

    • getLogLikelihood

      public double getLogLikelihood()
      The log likelihood of the regression
      Returns:
      a double

    • toString

      public String toString()
      Returns a string representation of the regression results.
      Overrides:
      toString in class Object