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:
  • 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