public class Kurtosis extends AbstractStorelessUnivariateStatistic implements java.io.Serializable
We use the following (unbiased) formula to define kurtosis:
kurtosis = { [n(n+1) / (n -1)(n - 2)(n-3)] sum[(x_i - mean)^4] / std^4 } - [3(n-1)^2 / (n-2)(n-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 < 4. Double.Nan
is returned when there is not sufficient data to compute the statistic.
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 |
---|
Kurtosis()
Construct a Kurtosis
|
Kurtosis(FourthMoment m4)
Construct a Kurtosis from an external moment
|
Kurtosis(Kurtosis original)
Copy constructor, creates a new
Kurtosis identical
to the original |
Modifier and Type | Method and Description |
---|---|
void |
clear()
Clears the internal state of the Statistic
|
Kurtosis |
copy()
Returns a copy of the statistic with the same internal state.
|
static void |
copy(Kurtosis source,
Kurtosis dest)
Copies source to dest.
|
double |
evaluate(double[] values,
int begin,
int length)
Returns the kurtosis 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 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, incrementAll
evaluate, getData, setData, setData
public Kurtosis()
public Kurtosis(FourthMoment m4)
m4
- external Momentpublic Kurtosis(Kurtosis original)
Kurtosis
identical
to the original
original
- the Kurtosis
instance to copypublic void increment(double d)
increment
in interface StorelessUnivariateStatistic
increment
in class AbstractStorelessUnivariateStatistic
d
- the new value.public double getResult()
getResult
in interface StorelessUnivariateStatistic
getResult
in class AbstractStorelessUnivariateStatistic
Double.NaN
if it
has been cleared or just instantiated.public void clear()
clear
in interface StorelessUnivariateStatistic
clear
in class AbstractStorelessUnivariateStatistic
public long getN()
getN
in interface StorelessUnivariateStatistic
public double evaluate(double[] values, int begin, int length)
See Kurtosis
for details on the computing algorithm.
Throws IllegalArgumentException
if the array is null.
evaluate
in interface UnivariateStatistic
evaluate
in class AbstractStorelessUnivariateStatistic
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includejava.lang.IllegalArgumentException
- if the input array is null or the array
index parameters are not validUnivariateStatistic.evaluate(double[], int, int)
public Kurtosis copy()
copy
in interface StorelessUnivariateStatistic
copy
in interface UnivariateStatistic
copy
in class AbstractStorelessUnivariateStatistic
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