org.jquantlib.math.statistics

Class IncrementalStatistics

java.lang.Object

org.jquantlib.math.statistics.GeneralStatistics

org.jquantlib.math.statistics.GenericGaussianStatistics

org.jquantlib.math.statistics.GaussianStatistics

org.jquantlib.math.statistics.GenericRiskStatistics

org.jquantlib.math.statistics.IncrementalStatistics

public class IncrementalStatistics
extends GenericRiskStatistics

Statistics tool based on incremental accumulation

It can accumulate a set of data and return statistics (e.g: mean, variance, skewness, kurtosis, error estimation, etc.)

Constructor Summary

Constructors

Constructor and Description
IncrementalStatistics()

Method Summary

Modifier and Type	Method and Description
void	add(double value) adds a datum to the set, possibly with a weight
void	add(double value, double weight)
void	addSequence(Array datum) adds a sequence of data to the set, with default weight
void	addSequence(Array datum, Array weights) adds a sequence of data to the set, each with its weight
void	addSequence(double[] datum) adds a sequence of data to the set, with default weight
void	addSequence(double[] datum, double[] weights) adds a sequence of data to the set, each with its weight
double	downsideDeviation() returns the downside deviation, defined as the square root of the downside variance.
double	downsideVariance() returns the downside variance, defined as , where = 0 if x > 0 and =1 if x <0
double	errorEstimate() returns the error estimate , defined as the square root of the ratio of the variance to the number of samples.
double	kurtosis() returns the excess kurtosis, defined as \frac{N^2(N+1)}{(N-1)(N-2)(N-3)} \frac{\left\langle \left(x-\langle x \rangle \right)^4 \right\rangle}{\sigma^4} - \frac{3(N-1)^2}{(N-2)(N-3)}.
double	max() returns the maximum sample value
double	mean() returns the mean, defined as \langle x \rangle = \frac{\sum w_i x_i}{\sum w_i}.
double	min() returns the minimum sample value
void	reset() resets the data to a null set
int	samples() number of samples collected
double	skewness() returns the skewness, defined as \frac{N^2}{(N-1)(N-2)} \frac{\left\langle \left( x-\langle x \rangle \right)^3 \right\rangle}{\sigma^3}.
double	standardDeviation() returns the standard deviation , defined as the square root of the variance.
double	variance() returns the variance, defined as \frac{N}{N-1} \left\langle \left( x-\langle x \rangle \right)^2 \right\rangle.
double	weightSum() sum of data weights

Methods inherited from class org.jquantlib.math.statistics.GenericRiskStatistics

averageShortfall, expectedShortfall, potentialUpside, regret, semiDeviation, semiVariance, shortfall, valueAtRisk

Methods inherited from class org.jquantlib.math.statistics.GenericGaussianStatistics

gaussianAverageShortfall, gaussianDownsideDeviation, gaussianDownsideVariance, gaussianExpectedShortfall, gaussianPercentile, gaussianPotentialUpside, gaussianRegret, gaussianShortfall, gaussianTopPercentile, gaussianValueAtRisk

Methods inherited from class org.jquantlib.math.statistics.GeneralStatistics

data, expectationValue, percentile, sort, topPercentile

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

IncrementalStatistics

public IncrementalStatistics()

Method Detail

samples

public int samples()

number of samples collected

Overrides:

samples in class GeneralStatistics

weightSum

public double weightSum()

sum of data weights

Overrides:

weightSum in class GeneralStatistics

mean

public double mean()

returns the mean, defined as

Overrides:

mean in class GeneralStatistics

variance

public double variance()

returns the variance, defined as

Overrides:

variance in class GeneralStatistics

standardDeviation

public double standardDeviation()

returns the standard deviation , defined as the square root of the variance.

Overrides:

standardDeviation in class GeneralStatistics

errorEstimate

public double errorEstimate()

returns the error estimate , defined as the square root of the ratio of the variance to the number of samples.

Overrides:

errorEstimate in class GeneralStatistics

downsideDeviation

public double downsideDeviation()

returns the downside deviation, defined as the square root of the downside variance.

Overrides:

downsideDeviation in class GenericRiskStatistics

downsideVariance

public double downsideVariance()

returns the downside variance, defined as , where = 0 if x > 0 and =1 if x <0

Overrides:

downsideVariance in class GenericRiskStatistics

skewness

public double skewness()

returns the skewness, defined as The above evaluates to 0 for a Gaussian distribution.

Overrides:

skewness in class GeneralStatistics

kurtosis

public double kurtosis()

returns the excess kurtosis, defined as The above evaluates to 0 for a Gaussian distribution.

Overrides:

kurtosis in class GeneralStatistics

min

public double min()

returns the minimum sample value

Overrides:

min in class GeneralStatistics

max

public double max()

returns the maximum sample value

Overrides:

max in class GeneralStatistics

addSequence

public void addSequence(double[] datum)

adds a sequence of data to the set, with default weight

Overrides:

addSequence in class GeneralStatistics

addSequence

public void addSequence(double[] datum,
                        double[] weights)

adds a sequence of data to the set, each with its weight

weights must be positive or null

Overrides:

addSequence in class GeneralStatistics

addSequence

public void addSequence(Array datum)

adds a sequence of data to the set, with default weight

Overrides:

addSequence in class GeneralStatistics

addSequence

public void addSequence(Array datum,
                        Array weights)

adds a sequence of data to the set, each with its weight

weights must be positive or null

Overrides:

addSequence in class GeneralStatistics

add

public void add(double value)

adds a datum to the set, possibly with a weight

weight must be positive or null

Overrides:

add in class GeneralStatistics

add

public void add(double value,
                double weight)

Overrides:

add in class GeneralStatistics

reset

public void reset()

resets the data to a null set

Overrides:

reset in class GeneralStatistics