org.apache.commons.math3.stat.descriptive.moment

## Class StandardDeviation

• All Implemented Interfaces:
Serializable, 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.

Version:
$Id: StandardDeviation.java 1416643 2012-12-03 19:37:14Z tn$
Serialized Form
• ### Constructor Summary

Constructors
Constructor and Description
StandardDeviation()
Constructs a StandardDeviation.
StandardDeviation(boolean isBiasCorrected)
Contructs a StandardDeviation with the specified value for the isBiasCorrected property.
StandardDeviation(boolean isBiasCorrected, SecondMoment m2)
Contructs 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

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.
static void copy(StandardDeviation source, StandardDeviation dest)
Copies source to dest.
double evaluate(double[] values)
Returns the Standard Deviation of the entries in the input array, or Double.NaN if the array is empty.
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()
void setBiasCorrected(boolean isBiasCorrected)
• ### 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)
Contructs 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)
Contructs 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
• ### Method Detail

• #### getN

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

Throws IllegalArgumentException if the array is null.

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.

Throws MathIllegalArgumentException if the array is null.

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.
• #### setBiasCorrected

public void setBiasCorrected(boolean isBiasCorrected)
Parameters:
isBiasCorrected - The isBiasCorrected to set.