Package org.apache.commons.statistics.descriptive

Class Mean

  • All Implemented Interfaces:
    DoubleConsumer, DoubleSupplier, IntSupplier, LongSupplier, DoubleStatistic, StatisticAccumulator<Mean>, StatisticResult
    public final class Mean
extends Object
implements DoubleStatistic, StatisticAccumulator<Mean>
    Computes the arithmetic mean of the available values. Uses the following definition of the sample mean:

    \[ \frac{1}{n} \sum_{i=1}^n x_i \]

    where \( n \) is the number of samples.

    • The result is NaN if no values are added.
    • The result is NaN if any of the values is NaN, or the values include infinite values of opposite sign.
    • The result is +/-infinity if values include infinite values of same sign.
    • The result is finite if all input values are finite.

    The accept(double) method uses the following recursive updating algorithm that protects the mean from overflow:

    1. Initialize \( m_1 \) using the first value
    2. For each additional value, update using
      \( m_{i+1} = m_i + (x - m_i) / (i + 1) \)

    The of(double...) method uses an extended precision sum if the sum is finite. Otherwise uses a corrected two-pass algorithm, starting with the recursive updating algorithm mentioned above, and then correcting this by adding the mean deviation of the data values from the one-pass mean (see Ling (1974)).

    Supports up to 263 (exclusive) observations. This implementation does not check for overflow of the count.

    This class is designed to work with (though does not require) streams.

    Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the accept or combine method, it must be synchronized externally.

    However, it is safe to use accept and combine as accumulator and combiner functions of Collector on a parallel stream, because the parallel implementation of Stream.collect() provides the necessary partitioning, isolation, and merging of results for safe and efficient parallel execution.

    References:

    • Ling, R.F. (1974) Comparison of Several Algorithms for Computing Sample Means and Variances. Journal of the American Statistical Association, 69, 859-866. doi: 10.2307/2286154
    Since:
    1.1
    See Also:
    Mean (Wikipedia)

    • Method Detail

      • create

        public static Mean create()
        Creates an instance.

        The initial result is NaN.

        Returns:
        Mean instance.

      • of

        public static Mean of​(double... values)
        Returns an instance populated using the input values.

        Note: Mean computed using accept may be different from this mean.

        See Mean for details on the computing algorithm.

        Parameters:
        values - Values.
        Returns:
        Mean instance.

      • accept

        public void accept​(double value)
        Updates the state of the statistic to reflect the addition of value.
        Specified by:
        accept in interface DoubleConsumer
        Parameters:
        value - Value.

      • getAsDouble

        public double getAsDouble()
        Gets the mean of all input values.

        When no values have been added, the result is NaN.

        Specified by:
        getAsDouble in interface DoubleSupplier
        Returns:
        mean of all values.