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org.hipparchus.stat.descriptive.moment

## Class Skewness

• All Implemented Interfaces:
Serializable, DoubleConsumer, StorelessUnivariateStatistic, UnivariateStatistic, MathArrays.Function

public class Skewness
extends AbstractStorelessUnivariateStatistic
implements Serializable
Computes the skewness of the available values.

We use the following (unbiased) formula to define skewness:

skewness = [n / (n -1) (n - 2)] sum[(x_i - mean)^3] / std^3

where n is the number of values, mean is the Mean and std is the StandardDeviation.

Note that this statistic is undefined for n < 3. Double.Nan is returned when there is not sufficient data to compute the statistic. Double.NaN may also be returned if the input includes NaN and / or infinite values.

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
• ### Field Summary

Fields
Modifier and Type Field and Description
protected boolean incMoment
Determines whether or not this statistic can be incremented or cleared.
protected org.hipparchus.stat.descriptive.moment.ThirdMoment moment
Third moment on which this statistic is based
• ### Constructor Summary

Constructors
Constructor and Description
Skewness()
Constructs a Skewness.
Skewness(Skewness original)
Copy constructor, creates a new Skewness identical to the original.
Skewness(org.hipparchus.stat.descriptive.moment.ThirdMoment m3)
Constructs a Skewness with an external moment.
• ### Method Summary

All Methods
Modifier and Type Method and Description
void clear()
Clears the internal state of the Statistic
Skewness copy()
Returns a copy of the statistic with the same internal state.
double evaluate(double[] values, int begin, int length)
Returns the Skewness of the entries in the specified portion of the input array.
long getN()
Returns the number of values that have been added.
double getResult()
Returns the value of the statistic based on the values that have been added.
void increment(double d)
Updates the internal state of the statistic to reflect the addition of the new value.
• ### Methods inherited from class org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic

equals, hashCode, toString
• ### Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait
• ### Methods inherited from interface org.hipparchus.stat.descriptive.StorelessUnivariateStatistic

accept, incrementAll, incrementAll
• ### Methods inherited from interface org.hipparchus.stat.descriptive.UnivariateStatistic

evaluate
• ### Methods inherited from interface java.util.function.DoubleConsumer

andThen
• ### Field Detail

• #### moment

protected final org.hipparchus.stat.descriptive.moment.ThirdMoment moment
Third moment on which this statistic is based
• #### incMoment

protected final 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

• #### Skewness

public Skewness()
Constructs a Skewness.
• #### Skewness

public Skewness(org.hipparchus.stat.descriptive.moment.ThirdMoment m3)
Constructs a Skewness with an external moment.
Parameters:
m3 - external moment
• #### Skewness

public Skewness(Skewness original)
throws NullArgumentException
Copy constructor, creates a new Skewness identical to the original.
Parameters:
original - the Skewness 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 Skewness(ThirdMoment) is used to create a Skewness, this method does nothing. In that case, the ThirdMoment should be incremented directly.

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

public double getResult()
Returns the value of the statistic based on the values that have been added.

See Skewness for the definition used in the computation.

Specified by:
getResult in interface StorelessUnivariateStatistic
Specified by:
getResult in class AbstractStorelessUnivariateStatistic
Returns:
the skewness of the available values.
• #### getN

public long getN()
Returns the number of values that have been added.
Specified by:
getN in interface StorelessUnivariateStatistic
Returns:
the number of values.
• #### clear

public void clear()
Clears the internal state of the Statistic
Specified by:
clear in interface StorelessUnivariateStatistic
Specified by:
clear in class AbstractStorelessUnivariateStatistic
• #### evaluate

public double evaluate(double[] values,
int begin,
int length)
throws MathIllegalArgumentException
Returns the Skewness of the entries in the specified portion of the input array.

See Skewness for the definition used in the computation.

Throws IllegalArgumentException if the array is null.

Specified by:
evaluate in interface StorelessUnivariateStatistic
Specified by:
evaluate in interface UnivariateStatistic
Specified by:
evaluate in interface MathArrays.Function
Parameters:
values - the input array
begin - the index of the first array element to include
length - the number of elements to include
Returns:
the skewness of the values or Double.NaN if length is less than 3
Throws:
MathIllegalArgumentException - if the array is null or the array index parameters are not valid
See Also:
UnivariateStatistic.evaluate(double[], int, int)
• #### copy

public Skewness 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
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