org.hipparchus.stat.descriptive.moment

## Class 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.

Serialized Form
• ### Constructor Summary

Constructors
Constructor and 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

All Methods
Modifier and Type Method and 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 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
• ### 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 StorelessUnivariateStatistic
Specified by:
evaluate in interface UnivariateStatistic
Specified by:
evaluate in interface MathArrays.Function
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
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