public class Mean extends AbstractStorelessUnivariateStatistic implements Serializable, WeightedEvaluation
Computes the arithmetic mean of a set of values. Uses the definitional formula:
mean = sum(x_i) / n
where n is the number of observations.
 
When increment(double) is used to add data incrementally from a
 stream of (unstored) values, the value of the statistic that
 getResult() returns is computed using the following recursive
 updating algorithm: 
m =  the first valuem = m + (new value - m) / (number of observations) If AbstractStorelessUnivariateStatistic.evaluate(double[]) is used to compute the mean of an array
 of stored values, a two-pass, corrected algorithm is used, starting with
 the definitional formula computed using the array of stored values and then
 correcting this by adding the mean deviation of the data values from the
 arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
 Sample Means and Variances," Robert F. Ling, Journal of the American
 Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866. 
  Returns Double.NaN if the dataset is empty. Note that
  Double.NaN may also be returned if the input includes NaN and / or infinite
  values.
 
increment() or
 clear() method, it must be synchronized externally.| Modifier and Type | Field and Description | 
|---|---|
| protected boolean | incMomentDetermines whether or not this statistic can be incremented or cleared. | 
| protected org.apache.commons.math3.stat.descriptive.moment.FirstMoment | momentFirst moment on which this statistic is based. | 
| Constructor and Description | 
|---|
| Mean()Constructs a Mean. | 
| Mean(org.apache.commons.math3.stat.descriptive.moment.FirstMoment m1)Constructs a Mean with an External Moment. | 
| Mean(Mean original)Copy constructor, creates a new  Meanidentical
 to theoriginal | 
| Modifier and Type | Method and Description | 
|---|---|
| void | clear()Clears the internal state of the Statistic | 
| Mean | copy()Returns a copy of the statistic with the same internal state. | 
| static void | copy(Mean source,
    Mean dest)Copies source to dest. | 
| double | evaluate(double[] values,
        double[] weights)Returns the weighted arithmetic mean of the entries in the input array. | 
| double | evaluate(double[] values,
        double[] weights,
        int begin,
        int length)Returns the weighted arithmetic mean of the entries in the specified portion of
 the input array, or  Double.NaNif the designated subarray
 is empty. | 
| double | evaluate(double[] values,
        int begin,
        int length)Returns the arithmetic mean of the entries in the specified portion of
 the input array, or  Double.NaNif the designated subarray
 is empty. | 
| long | getN()Returns the number of values that have been added. | 
| double | getResult()Returns the current value of the Statistic. | 
| void | increment(double d)Updates the internal state of the statistic to reflect the addition of the new value. | 
equals, evaluate, hashCode, incrementAll, incrementAllevaluate, getData, getDataRef, setData, setData, test, test, test, testprotected org.apache.commons.math3.stat.descriptive.moment.FirstMoment moment
protected boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
public Mean()
public Mean(org.apache.commons.math3.stat.descriptive.moment.FirstMoment m1)
m1 - the momentpublic Mean(Mean original) throws NullArgumentException
Mean identical
 to the originaloriginal - the Mean instance to copyNullArgumentException - if original is nullpublic void increment(double d)
Note that when Mean(FirstMoment) is used to
 create a Mean, this method does nothing. In that case, the
 FirstMoment should be incremented directly.
increment in interface StorelessUnivariateStatisticincrement in class AbstractStorelessUnivariateStatisticd - the new value.public void clear()
clear in interface StorelessUnivariateStatisticclear in class AbstractStorelessUnivariateStatisticpublic double getResult()
getResult in interface StorelessUnivariateStatisticgetResult in class AbstractStorelessUnivariateStatisticDouble.NaN if it
 has been cleared or just instantiated.public long getN()
getN in interface StorelessUnivariateStatisticpublic double evaluate(double[] values,
              int begin,
              int length)
                throws MathIllegalArgumentException
Double.NaN if the designated subarray
 is empty.
 
 Throws IllegalArgumentException if the array is null.
 See Mean for details on the computing algorithm.
evaluate in interface UnivariateStatisticevaluate in interface MathArrays.Functionevaluate in class AbstractStorelessUnivariateStatisticvalues - the input arraybegin - index of the first array element to includelength - the number of elements to includeMathIllegalArgumentException - if the array is null or the array index
  parameters are not validUnivariateStatistic.evaluate(double[], int, int)public double evaluate(double[] values,
              double[] weights,
              int begin,
              int length)
                throws MathIllegalArgumentException
Double.NaN if the designated subarray
 is empty.
 
 Throws IllegalArgumentException if either array is null.
 See Mean for details on the computing algorithm. The two-pass algorithm
 described above is used here, with weights applied in computing both the original
 estimate and the correction factor.
 Throws IllegalArgumentException if any of the following are true:
 
evaluate in interface WeightedEvaluationvalues - the input arrayweights - the weights arraybegin - index of the first array element to includelength - the number of elements to includeMathIllegalArgumentException - if the parameters are not validpublic double evaluate(double[] values,
              double[] weights)
                throws MathIllegalArgumentException
 Throws MathIllegalArgumentException if either array is null.
 See Mean for details on the computing algorithm. The two-pass algorithm
 described above is used here, with weights applied in computing both the original
 estimate and the correction factor.
 Throws MathIllegalArgumentException if any of the following are true:
 
evaluate in interface WeightedEvaluationvalues - the input arrayweights - the weights arrayMathIllegalArgumentException - if the parameters are not validpublic Mean copy()
copy in interface StorelessUnivariateStatisticcopy in interface UnivariateStatisticcopy in class AbstractStorelessUnivariateStatisticpublic static void copy(Mean source, Mean dest) throws NullArgumentException
Neither source nor dest can be null.
source - Mean to copydest - Mean to copy toNullArgumentException - if either source or dest is nullCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.