org.apache.commons.math3.stat.descriptive.moment
Class Mean

java.lang.Object
  extended by org.apache.commons.math3.stat.descriptive.AbstractUnivariateStatistic
      extended by org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic
          extended by org.apache.commons.math3.stat.descriptive.moment.Mean
All Implemented Interfaces:
Serializable, StorelessUnivariateStatistic, UnivariateStatistic, WeightedEvaluation, MathArrays.Function

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:

  1. Initialize m = the first value
  2. For each additional value, update using
    m = 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 this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the increment() or clear() method, it must be synchronized externally.

Version:
$Id: Mean.java 1416643 2012-12-03 19:37:14Z tn $
See Also:
Serialized Form

Field Summary
protected  boolean incMoment
          Determines whether or not this statistic can be incremented or cleared.
protected  org.apache.commons.math3.stat.descriptive.moment.FirstMoment moment
          First moment on which this statistic is based.
 
Constructor Summary
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 Mean identical to the original
 
Method Summary
 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.NaN if 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.NaN if 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.
 
Methods inherited from class org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic
equals, evaluate, hashCode, incrementAll, incrementAll
 
Methods inherited from class org.apache.commons.math3.stat.descriptive.AbstractUnivariateStatistic
evaluate, getData, getDataRef, setData, setData, test, test, test, test
 
Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

moment

protected org.apache.commons.math3.stat.descriptive.moment.FirstMoment moment
First moment on which this statistic is based.


incMoment

protected boolean incMoment
Determines whether or not this statistic can be incremented or cleared.

Statistics based on (constructed from) external moments cannot be incremented or cleared.

Constructor Detail

Mean

public Mean()
Constructs a Mean.


Mean

public Mean(org.apache.commons.math3.stat.descriptive.moment.FirstMoment m1)
Constructs a Mean with an External Moment.

Parameters:
m1 - the moment

Mean

public Mean(Mean original)
     throws NullArgumentException
Copy constructor, creates a new Mean identical to the original

Parameters:
original - the Mean instance to copy
Throws:
NullArgumentException - if original is null
Method Detail

increment

public void increment(double d)
Updates the internal state of the statistic to reflect the addition of the new value.

Note that when Mean(FirstMoment) is used to create a Mean, this method does nothing. In that case, the FirstMoment should be incremented directly.

Specified by:
increment in interface StorelessUnivariateStatistic
Specified by:
increment in class AbstractStorelessUnivariateStatistic
Parameters:
d - the new value.

clear

public void clear()
Clears the internal state of the Statistic

Specified by:
clear in interface StorelessUnivariateStatistic
Specified by:
clear in class AbstractStorelessUnivariateStatistic

getResult

public double getResult()
Returns the current value of the Statistic.

Specified by:
getResult in interface StorelessUnivariateStatistic
Specified by:
getResult in class AbstractStorelessUnivariateStatistic
Returns:
value of the statistic, Double.NaN if it has been cleared or just instantiated.

getN

public long getN()
Returns the number of values that have been added.

Specified by:
getN in interface StorelessUnivariateStatistic
Returns:
the number of values.

evaluate

public double evaluate(double[] values,
                       int begin,
                       int length)
                throws MathIllegalArgumentException
Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

Throws IllegalArgumentException if the array is null.

See Mean for details on the computing algorithm.

Specified by:
evaluate in interface UnivariateStatistic
Specified by:
evaluate in interface MathArrays.Function
Overrides:
evaluate in class AbstractStorelessUnivariateStatistic
Parameters:
values - the input array
begin - index of the first array element to include
length - the number of elements to include
Returns:
the mean of the values or Double.NaN if length = 0
Throws:
MathIllegalArgumentException - if the array is null or the array index parameters are not valid
See Also:
UnivariateStatistic.evaluate(double[], int, int)

evaluate

public double evaluate(double[] values,
                       double[] weights,
                       int begin,
                       int length)
                throws MathIllegalArgumentException
Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or 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:

Specified by:
evaluate in interface WeightedEvaluation
Parameters:
values - the input array
weights - the weights array
begin - index of the first array element to include
length - the number of elements to include
Returns:
the mean of the values or Double.NaN if length = 0
Throws:
MathIllegalArgumentException - if the parameters are not valid
Since:
2.1

evaluate

public double evaluate(double[] values,
                       double[] weights)
                throws MathIllegalArgumentException
Returns the weighted arithmetic mean of the entries in the input array.

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:

Specified by:
evaluate in interface WeightedEvaluation
Parameters:
values - the input array
weights - the weights array
Returns:
the mean of the values or Double.NaN if length = 0
Throws:
MathIllegalArgumentException - if the parameters are not valid
Since:
2.1

copy

public Mean copy()
Returns a copy of the statistic with the same internal state.

Specified by:
copy in interface StorelessUnivariateStatistic
Specified by:
copy in interface UnivariateStatistic
Specified by:
copy in class AbstractStorelessUnivariateStatistic
Returns:
a copy of the statistic

copy

public static void copy(Mean source,
                        Mean dest)
                 throws NullArgumentException
Copies source to dest.

Neither source nor dest can be null.

Parameters:
source - Mean to copy
dest - Mean to copy to
Throws:
NullArgumentException - if either source or dest is null


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