Package org.hipparchus.stat.descriptive.moment

Class StandardDeviation

java.lang.Object

org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic

org.hipparchus.stat.descriptive.moment.StandardDeviation

All Implemented Interfaces:

Serializable, DoubleConsumer, StorelessUnivariateStatistic, UnivariateStatistic, MathArrays.Function

public class StandardDeviation
extends AbstractStorelessUnivariateStatistic
implements Serializable

Computes the sample standard deviation.

The standard deviation is the positive square root of the variance. This implementation wraps a Variance instance.

The isBiasCorrected property of the wrapped Variance instance is exposed, so that this class can be used to compute both the "sample standard deviation" (the square root of the bias-corrected "sample variance") or the "population standard deviation" (the square root of the non-bias-corrected "population variance"). See Variance for more information.

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	Description
StandardDeviation()	Constructs a StandardDeviation.
StandardDeviation(boolean isBiasCorrected)	Constructs a StandardDeviation with the specified value for the isBiasCorrected property.
StandardDeviation(boolean isBiasCorrected, SecondMoment m2)	Constructs a StandardDeviation with the specified value for the isBiasCorrected property and the supplied external moment.
StandardDeviation(SecondMoment m2)	Constructs a StandardDeviation from an external second moment.
StandardDeviation(StandardDeviation original)	Copy constructor, creates a new StandardDeviation identical to the original.

Method Summary

Modifier and Type	Method	Description
void	clear()	Clears the internal state of the Statistic
StandardDeviation	copy()	Returns a copy of the statistic with the same internal state.
double	evaluate(double[] values, double mean)	Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
double	evaluate(double[] values, double mean, int begin, int length)	Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
double	evaluate(double[] values, int begin, int length)	Returns the Standard Deviation 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.
boolean	isBiasCorrected()
StandardDeviation	withBiasCorrection(boolean biasCorrection)	Returns a new copy of this standard deviation with the given bias correction setting.

Methods inherited from class org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic

equals, hashCode, toString

Methods inherited from interface java.util.function.DoubleConsumer

andThen

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

Constructor Detail

StandardDeviation

public StandardDeviation()

Constructs a StandardDeviation. Sets the underlying Variance instance's isBiasCorrected property to true.

StandardDeviation

public StandardDeviation(SecondMoment m2)

Constructs a StandardDeviation from an external second moment.

Parameters:

m2 - the external moment

StandardDeviation

public StandardDeviation(boolean isBiasCorrected)

Constructs a StandardDeviation with the specified value for the isBiasCorrected property. If this property is set to true, the Variance used in computing results will use the bias-corrected, or "sample" formula. See Variance for details.

Parameters:

isBiasCorrected - whether or not the variance computation will use the bias-corrected formula

StandardDeviation

public StandardDeviation(boolean isBiasCorrected,
                         SecondMoment m2)

Constructs a StandardDeviation with the specified value for the isBiasCorrected property and the supplied external moment. If isBiasCorrected is set to true, the Variance used in computing results will use the bias-corrected, or "sample" formula. See Variance for details.

Parameters:

isBiasCorrected - whether or not the variance computation will use the bias-corrected formula

m2 - the external moment

StandardDeviation

public StandardDeviation(StandardDeviation original)
                  throws NullArgumentException

Copy constructor, creates a new StandardDeviation identical to the original.

Parameters:

original - the StandardDeviation 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.

Specified by:

increment in interface StorelessUnivariateStatistic

Specified by:

increment in class AbstractStorelessUnivariateStatistic

Parameters:

d - the new value.

getN

public long getN()

Returns the number of values that have been added.

Specified by:

getN in interface StorelessUnivariateStatistic

Returns:

the number of values.

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.

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 Standard Deviation of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

Returns 0 for a single-value (i.e. length = 1) sample.

Does not change the internal state of the statistic.

Specified by:

evaluate in interface MathArrays.Function

Specified by:

evaluate in interface StorelessUnivariateStatistic

Specified by:

evaluate in interface UnivariateStatistic

Parameters:

values - the input array

begin - index of the first array element to include

length - the number of elements to include

Returns:

the standard deviation 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 mean,
                       int begin,
                       int length)
                throws MathIllegalArgumentException

Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value. Returns Double.NaN if the designated subarray is empty.

Returns 0 for a single-value (i.e. length = 1) sample.

The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.

Does not change the internal state of the statistic.

Parameters:

values - the input array

mean - the precomputed mean value

begin - index of the first array element to include

length - the number of elements to include

Returns:

the standard deviation of the values or Double.NaN if length = 0

Throws:

MathIllegalArgumentException - if the array is null or the array index parameters are not valid

evaluate

public double evaluate(double[] values,
                       double mean)
                throws MathIllegalArgumentException

Returns the Standard Deviation of the entries in the input array, using the precomputed mean value. Returns Double.NaN if the designated subarray is empty.

Returns 0 for a single-value (i.e. length = 1) sample.

The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.

Does not change the internal state of the statistic.

Parameters:

values - the input array

mean - the precomputed mean value

Returns:

the standard deviation of the values or Double.NaN if length = 0

Throws:

MathIllegalArgumentException - if the array is null

isBiasCorrected

public boolean isBiasCorrected()

Returns:

Returns the isBiasCorrected.

withBiasCorrection

public StandardDeviation withBiasCorrection(boolean biasCorrection)

Returns a new copy of this standard deviation with the given bias correction setting.

Parameters:

biasCorrection - The bias correction flag to set.

Returns:

a copy of this instance with the given bias correction setting

copy

public StandardDeviation 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