Mean (The Adobe AEM Quickstart and Web Application.)

java.lang.Object
- org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
- - org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  - - org.apache.commons.math.stat.descriptive.moment.Mean

All Implemented Interfaces:

java.io.Serializable, StorelessUnivariateStatistic, UnivariateStatistic, WeightedEvaluation
```
public class Mean
extends AbstractStorelessUnivariateStatistic
implements java.io.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.
See Also:

Serialized Form

Constructor Summary

Constructors
Constructor and Description
`Mean()` Constructs a Mean.
`Mean(FirstMoment m1)` Constructs a Mean with an External Moment.
`Mean(Mean original)` Copy constructor, creates a new `Mean` identical to the `original`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
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.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.math.stat.descriptive.AbstractStorelessUnivariateStatistic
equals, evaluate, hashCode, incrementAll, incrementAll

Methods inherited from class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
evaluate, getData, setData, setData

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Mean
```
public Mean()
```
    Constructs a Mean.
  - Mean
```
public Mean(FirstMoment m1)
```
    Constructs a Mean with an External Moment.
    
    Parameters:
    
    m1 - the moment
  - Mean
```
public Mean(Mean original)
```
    Copy constructor, creates a new Mean identical to the original
    
    Parameters:
    
    original - the Mean instance to copy
- Method Detail
  - increment
```
public void increment(double d)
```
    Updates the internal state of the statistic to reflect the addition of the new value.
    
    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)
```
    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
    
    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:
    
    java.lang.IllegalArgumentException - 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)
```
    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:
    - the values array is null
    - the weights array is null
    - the weights array does not have the same length as the values array
    - the weights array contains one or more infinite values
    - the weights array contains one or more NaN values
    - the weights array contains negative values
    - the start and length arguments do not determine a valid array
    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:
    
    java.lang.IllegalArgumentException - if the parameters are not valid
    
    Since:
    
    2.1
  - evaluate
```
public double evaluate(double[] values,
                       double[] weights)
```
    Returns the weighted arithmetic mean of the entries in the input array.
    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:
    - the values array is null
    - the weights array is null
    - the weights array does not have the same length as the values array
    - the weights array contains one or more infinite values
    - the weights array contains one or more NaN values
    - the weights array contains negative values
    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:
    
    java.lang.IllegalArgumentException - 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)
```
    Copies source to dest.
    Neither source nor dest can be null.
    
    Parameters:
    
    source - Mean to copy
    
    dest - Mean to copy to
    
    Throws:
    
    java.lang.NullPointerException - if either source or dest is null

Class Mean

Constructor Summary

Method Summary

Methods inherited from class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic

Methods inherited from class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic

Methods inherited from class java.lang.Object

Constructor Detail

Mean

Mean

Mean

Method Detail

increment

clear

getResult

getN

evaluate

evaluate

evaluate

copy

copy