Package org.hipparchus.stat.descriptive

Interface WeightedEvaluation

All Known Implementing Classes:
Mean, Product, Sum, Variance
public interface WeightedEvaluation
Weighted evaluation for statistics.

  • Method Summary

    Modifier and Type
    Method
    Description
    default double
    evaluate(double[] values, double[] weights)
    Returns the result of evaluating the statistic over the input array, using the supplied weights.
    double
    evaluate(double[] values, double[] weights, int begin, int length)
    Returns the result of evaluating the statistic over the specified entries in the input array, using corresponding entries in the supplied weights array.

  • Method Details

    • evaluate

      default double evaluate(double[] values, double[] weights) throws MathIllegalArgumentException
      Returns the result of evaluating the statistic over the input array, using the supplied weights.

      The default implementation delegates to evaluate(double[], double[], int, int) in the natural way.

      Parameters:
      values - input array
      weights - array of weights
      Returns:
      the value of the weighted statistic applied to the input array
      Throws:
      MathIllegalArgumentException - if either array is null, lengths do not match, weights contain NaN, negative or infinite values, or weights does not include at least on positive value

    • evaluate

      double evaluate(double[] values, double[] weights, int begin, int length) throws MathIllegalArgumentException
      Returns the result of evaluating the statistic over the specified entries in the input array, using corresponding entries in the supplied weights array.
      Parameters:
      values - the input array
      weights - array of weights
      begin - the index of the first element to include
      length - the number of elements to include
      Returns:
      the value of the weighted statistic applied to the included array entries
      Throws:
      MathIllegalArgumentException - if either array is null, lengths do not match, indices are invalid, weights contain NaN, negative or infinite values, or weights does not include at least on positive value