Class StandardDeviation
- java.lang.Object
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- org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic
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- org.hipparchus.stat.descriptive.moment.StandardDeviation
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- 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"). SeeVariance
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()
orclear()
method, it must be synchronized externally.- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor Description StandardDeviation()
Constructs a StandardDeviation.StandardDeviation(boolean isBiasCorrected)
Constructs a StandardDeviation with the specified value for theisBiasCorrected
property.StandardDeviation(boolean isBiasCorrected, SecondMoment m2)
Constructs a StandardDeviation with the specified value for theisBiasCorrected
property and the supplied external moment.StandardDeviation(SecondMoment m2)
Constructs a StandardDeviation from an external second moment.StandardDeviation(StandardDeviation original)
Copy constructor, creates a newStandardDeviation
identical to theoriginal
.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
clear()
Clears the internal state of the StatisticStandardDeviation
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, orDouble.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()
Check if bias is corrected.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
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Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
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Methods inherited from interface java.util.function.DoubleConsumer
andThen
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Methods inherited from interface org.hipparchus.stat.descriptive.StorelessUnivariateStatistic
accept, incrementAll, incrementAll
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Methods inherited from interface org.hipparchus.stat.descriptive.UnivariateStatistic
evaluate
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Constructor Detail
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StandardDeviation
public StandardDeviation()
Constructs a StandardDeviation. Sets the underlyingVariance
instance'sisBiasCorrected
property to true.
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StandardDeviation
public StandardDeviation(SecondMoment m2)
Constructs a StandardDeviation from an external second moment.- Parameters:
m2
- the external moment
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StandardDeviation
public StandardDeviation(boolean isBiasCorrected)
Constructs a StandardDeviation with the specified value for theisBiasCorrected
property. If this property is set totrue
, theVariance
used in computing results will use the bias-corrected, or "sample" formula. SeeVariance
for details.- Parameters:
isBiasCorrected
- whether or not the variance computation will use the bias-corrected formula
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StandardDeviation
public StandardDeviation(boolean isBiasCorrected, SecondMoment m2)
Constructs a StandardDeviation with the specified value for theisBiasCorrected
property and the supplied external moment. IfisBiasCorrected
is set totrue
, theVariance
used in computing results will use the bias-corrected, or "sample" formula. SeeVariance
for details.- Parameters:
isBiasCorrected
- whether or not the variance computation will use the bias-corrected formulam2
- the external moment
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StandardDeviation
public StandardDeviation(StandardDeviation original) throws NullArgumentException
Copy constructor, creates a newStandardDeviation
identical to theoriginal
.- Parameters:
original
- theStandardDeviation
instance to copy- Throws:
NullArgumentException
- if original is null
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Method Detail
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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 interfaceStorelessUnivariateStatistic
- Specified by:
increment
in classAbstractStorelessUnivariateStatistic
- Parameters:
d
- the new value.
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getN
public long getN()
Returns the number of values that have been added.- Specified by:
getN
in interfaceStorelessUnivariateStatistic
- Returns:
- the number of values.
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getResult
public double getResult()
Returns the current value of the Statistic.- Specified by:
getResult
in interfaceStorelessUnivariateStatistic
- Specified by:
getResult
in classAbstractStorelessUnivariateStatistic
- Returns:
- value of the statistic,
Double.NaN
if it has been cleared or just instantiated.
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clear
public void clear()
Clears the internal state of the Statistic- Specified by:
clear
in interfaceStorelessUnivariateStatistic
- Specified by:
clear
in classAbstractStorelessUnivariateStatistic
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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, orDouble.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 interfaceMathArrays.Function
- Specified by:
evaluate
in interfaceStorelessUnivariateStatistic
- Specified by:
evaluate
in interfaceUnivariateStatistic
- Parameters:
values
- the input arraybegin
- index of the first array element to includelength
- 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)
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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. ReturnsDouble.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 arraymean
- the precomputed mean valuebegin
- index of the first array element to includelength
- 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
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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. ReturnsDouble.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 arraymean
- the precomputed mean value- Returns:
- the standard deviation of the values or Double.NaN if length = 0
- Throws:
MathIllegalArgumentException
- if the array is null
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isBiasCorrected
public boolean isBiasCorrected()
Check if bias is corrected.- Returns:
- Returns the isBiasCorrected.
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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
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copy
public StandardDeviation copy()
Returns a copy of the statistic with the same internal state.- Specified by:
copy
in interfaceStorelessUnivariateStatistic
- Specified by:
copy
in interfaceUnivariateStatistic
- Specified by:
copy
in classAbstractStorelessUnivariateStatistic
- Returns:
- a copy of the statistic
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