public class Skewness extends AbstractStorelessUnivariateStatistic implements java.io.Serializable
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 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.
| Constructor and Description |
|---|
Skewness()
Constructs a Skewness
|
Skewness(Skewness original)
Copy constructor, creates a new
Skewness identical
to the original |
Skewness(ThirdMoment m3)
Constructs a Skewness with an external moment
|
| 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.
|
static void |
copy(Skewness source,
Skewness dest)
Copies source to dest.
|
double |
evaluate(double[] values,
int begin,
int length)
Returns the Skewness of the entries in the specifed 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.
|
equals, evaluate, hashCode, incrementAll, incrementAllevaluate, getData, setData, setDatapublic Skewness()
public Skewness(ThirdMoment m3)
m3 - external momentpublic Skewness(Skewness original)
Skewness identical
to the originaloriginal - the Skewness instance to copypublic void increment(double d)
increment in interface StorelessUnivariateStatisticincrement in class AbstractStorelessUnivariateStatisticd - the new value.public double getResult()
See Skewness for the definition used in the computation.
getResult in interface StorelessUnivariateStatisticgetResult in class AbstractStorelessUnivariateStatisticpublic long getN()
getN in interface StorelessUnivariateStatisticpublic void clear()
clear in interface StorelessUnivariateStatisticclear in class AbstractStorelessUnivariateStatisticpublic double evaluate(double[] values,
int begin,
int length)
See Skewness for the definition used in the computation.
Throws IllegalArgumentException if the array is null.
evaluate in interface UnivariateStatisticevaluate in class AbstractStorelessUnivariateStatisticvalues - the input arraybegin - the index of the first array element to includelength - the number of elements to includejava.lang.IllegalArgumentException - if the array is null or the array index
parameters are not validUnivariateStatistic.evaluate(double[], int, int)public Skewness copy()
copy in interface StorelessUnivariateStatisticcopy in interface UnivariateStatisticcopy in class AbstractStorelessUnivariateStatisticCopyright © 2010 - 2023 Adobe. All Rights Reserved