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## org.apache.commons.math3.stat.descriptive.moment
Class SemiVariance

    java.lang.Object
      org.apache.commons.math3.stat.descriptive.AbstractUnivariateStatistic
          org.apache.commons.math3.stat.descriptive.moment.SemiVariance

All Implemented Interfaces:
  Serializable, UnivariateStatistic, MathArrays.Function

    public class SemiVariance

extends AbstractUnivariateStatistic
implements Serializable

Computes the semivariance of a set of values with respect to a given cutoff value. We define the downside semivariance of a set of values `x` against the cutoff value `cutoff` to be
`Σ (x[i] - target)2 / df`
where the sum is taken over all `i` such that `x[i] < cutoff` and `df` is the length of `x` (non-bias-corrected) or one less than this number (bias corrected). The upside semivariance is defined similarly, with the sum taken over values of `x` that exceed the cutoff value.

The cutoff value defaults to the mean, bias correction defaults to `true` and the "variance direction" (upside or downside) defaults to downside. The variance direction and bias correction may be set using property setters or their values can provided as parameters to `evaluate(double[], double, Direction, boolean, int, int)`.

If the input array is null, `evaluate` methods throw `IllegalArgumentException.` If the array has length 1, `0` is returned, regardless of the value of the `cutoff.`

Note that this class is not intended to be threadsafe. If multiple threads access an instance of this class concurrently, and one or more of these threads invoke property setters, external synchronization must be provided to ensure correct results.

Since:
  2.1
Version:
  $Id: SemiVariance.java 1385386 2012-09-16 22:11:15Z psteitz $
See Also:
  Serialized Form

Nested Class Summary
`static class` | `SemiVariance.Direction` The direction of the semivariance - either upside or downside.

Field Summary
`static SemiVariance.Direction` | `DOWNSIDE_VARIANCE` The DOWNSIDE Direction is used to specify that the observations below the cutoff point will be used to calculate SemiVariance
`static SemiVariance.Direction` | `UPSIDE_VARIANCE` The UPSIDE Direction is used to specify that the observations above the cutoff point will be used to calculate SemiVariance.

Constructor Summary
`SemiVariance()` Constructs a SemiVariance with default (true) `biasCorrected` property and default (Downside) `varianceDirection` property.
`SemiVariance(boolean biasCorrected)` Constructs a SemiVariance with the specified `biasCorrected` property and default (Downside) `varianceDirection` property.
`SemiVariance(boolean corrected, SemiVariance.Direction direction)` Constructs a SemiVariance with the specified `isBiasCorrected` property and the specified `Direction` property.
`SemiVariance(SemiVariance.Direction direction)` Constructs a SemiVariance with the specified `Direction` property and default (true) `biasCorrected` property
`SemiVariance(SemiVariance original)` Copy constructor, creates a new `SemiVariance` identical to the `original`

Method Summary
`SemiVariance` | `copy()` Returns a copy of the statistic with the same internal state.
`static void` | `copy(SemiVariance source, SemiVariance dest)` Copies source to dest.
`double` | `evaluate(double[] values, double cutoff)` Returns the `SemiVariance` of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.
`double` | `evaluate(double[] values, double cutoff, SemiVariance.Direction direction)` Returns the `SemiVariance` of the designated values against the cutoff in the given direction, using the current value of the biasCorrection instance property.
`double` | `evaluate(double[] values, double cutoff, SemiVariance.Direction direction, boolean corrected, int start, int length)` Returns the `SemiVariance` of the designated values against the cutoff in the given direction with the provided bias correction.
`double` | `evaluate(double[] values, int start, int length)` Returns the `SemiVariance` of the designated values against the mean, using instance properties varianceDirection and biasCorrection.
`double` | `evaluate(double[] values, SemiVariance.Direction direction)` This method calculates `SemiVariance` for the entire array against the mean, using the current value of the biasCorrection instance property.
`SemiVariance.Direction` | `getVarianceDirection()` Returns the varianceDirection property.
`boolean` | `isBiasCorrected()` Returns true iff biasCorrected property is set to true.
`void` | `setBiasCorrected(boolean biasCorrected)` Sets the biasCorrected property.
`void` | `setVarianceDirection(SemiVariance.Direction varianceDirection)` Sets the variance direction

Methods inherited from class org.apache.commons.math3.stat.descriptive.AbstractUnivariateStatistic
`evaluate, evaluate, getData, getDataRef, setData, setData, test, test, test, test`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### UPSIDE_VARIANCE

    public static final SemiVariance.Direction UPSIDE_VARIANCE

  The UPSIDE Direction is used to specify that the observations above the cutoff point will be used to calculate SemiVariance.

### DOWNSIDE_VARIANCE

    public static final SemiVariance.Direction DOWNSIDE_VARIANCE

  The DOWNSIDE Direction is used to specify that the observations below the cutoff point will be used to calculate SemiVariance

Constructor Detail

### SemiVariance

    public SemiVariance()

  Constructs a SemiVariance with default (true) `biasCorrected` property and default (Downside) `varianceDirection` property.

### SemiVariance

    public SemiVariance(boolean biasCorrected)

  Constructs a SemiVariance with the specified `biasCorrected` property and default (Downside) `varianceDirection` property.

  Parameters:
    `biasCorrected` - setting for bias correction - true means bias will be corrected and is equivalent to using the argumentless constructor

### SemiVariance

    public SemiVariance(SemiVariance.Direction direction)

  Constructs a SemiVariance with the specified `Direction` property and default (true) `biasCorrected` property

  Parameters:
    `direction` - setting for the direction of the SemiVariance to calculate

### SemiVariance

    public SemiVariance(boolean corrected,
                        SemiVariance.Direction direction)

  Constructs a SemiVariance with the specified `isBiasCorrected` property and the specified `Direction` property.

  Parameters:
    `corrected` - setting for bias correction - true means bias will be corrected and is equivalent to using the argumentless constructor
    `direction` - setting for the direction of the SemiVariance to calculate

### SemiVariance

    public SemiVariance(SemiVariance original)
                 throws NullArgumentException

  Copy constructor, creates a new `SemiVariance` identical to the `original`

  Parameters:
    `original` - the `SemiVariance` instance to copy
  Throws:
    `NullArgumentException` - if original is null

Method Detail

### copy

    public SemiVariance copy()

  Returns a copy of the statistic with the same internal state.

  Specified by:
    `copy` in interface `UnivariateStatistic`
  Specified by:
    `copy` in class `AbstractUnivariateStatistic`
  Returns:
    a copy of the statistic

### copy

    public static void copy(SemiVariance source,
                            SemiVariance dest)
                     throws NullArgumentException

  Copies source to dest.

  Neither source nor dest can be null.

  Parameters:
    `source` - SemiVariance to copy
    `dest` - SemiVariance to copy to
  Throws:
    `NullArgumentException` - if either source or dest is null

### evaluate

    public double evaluate(double[] values,
                           int start,
                           int length)
                    throws MathIllegalArgumentException

  Returns the `SemiVariance` of the designated values against the mean, using instance properties varianceDirection and biasCorrection.

  Returns `NaN` if the array is empty and throws `IllegalArgumentException` if the array is null.

  Specified by:
    `evaluate` in interface `UnivariateStatistic`
  Specified by:
    `evaluate` in interface `MathArrays.Function`
  Specified by:
    `evaluate` in class `AbstractUnivariateStatistic`
  Parameters:
    `values` - the input array
    `start` - index of the first array element to include
    `length` - the number of elements to include
  Returns:
    the SemiVariance
  Throws:
    `MathIllegalArgumentException` - if the parameters are not valid

### evaluate

    public double evaluate(double[] values,
                           SemiVariance.Direction direction)
                    throws MathIllegalArgumentException

  This method calculates `SemiVariance` for the entire array against the mean, using the current value of the biasCorrection instance property.

  Parameters:
    `values` - the input array
    `direction` - the `SemiVariance.Direction` of the semivariance
  Returns:
    the SemiVariance
  Throws:
    `MathIllegalArgumentException` - if values is null

### evaluate

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

  Returns the `SemiVariance` of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.

  Returns `NaN` if the array is empty and throws `MathIllegalArgumentException` if the array is null.

  Parameters:
    `values` - the input array
    `cutoff` - the reference point
  Returns:
    the SemiVariance
  Throws:
    `MathIllegalArgumentException` - if values is null

### evaluate

    public double evaluate(double[] values,
                           double cutoff,
                           SemiVariance.Direction direction)
                    throws MathIllegalArgumentException

  Returns the `SemiVariance` of the designated values against the cutoff in the given direction, using the current value of the biasCorrection instance property.

  Returns `NaN` if the array is empty and throws `MathIllegalArgumentException` if the array is null.

  Parameters:
    `values` - the input array
    `cutoff` - the reference point
    `direction` - the `SemiVariance.Direction` of the semivariance
  Returns:
    the SemiVariance
  Throws:
    `MathIllegalArgumentException` - if values is null

### evaluate

    public double evaluate(double[] values,
                           double cutoff,
                           SemiVariance.Direction direction,
                           boolean corrected,
                           int start,
                           int length)
                    throws MathIllegalArgumentException

  Returns the `SemiVariance` of the designated values against the cutoff in the given direction with the provided bias correction.

  Returns `NaN` if the array is empty and throws `IllegalArgumentException` if the array is null.

  Parameters:
    `values` - the input array
    `cutoff` - the reference point
    `direction` - the `SemiVariance.Direction` of the semivariance
    `corrected` - the BiasCorrection flag
    `start` - index of the first array element to include
    `length` - the number of elements to include
  Returns:
    the SemiVariance
  Throws:
    `MathIllegalArgumentException` - if the parameters are not valid

### isBiasCorrected

    public boolean isBiasCorrected()

  Returns true iff biasCorrected property is set to true.

  Returns:
    the value of biasCorrected.

### setBiasCorrected

    public void setBiasCorrected(boolean biasCorrected)

  Sets the biasCorrected property.

  Parameters:
    `biasCorrected` - new biasCorrected property value

### getVarianceDirection

    public SemiVariance.Direction getVarianceDirection()

  Returns the varianceDirection property.

  Returns:
    the varianceDirection

### setVarianceDirection

    public void setVarianceDirection(SemiVariance.Direction varianceDirection)

  Sets the variance direction

  Parameters:
    `varianceDirection` - the direction of the semivariance

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