Uses of Interface
org.apache.commons.math3.stat.descriptive.UnivariateStatistic

Packages that use UnivariateStatistic

Package	Description
org.apache.commons.math3.stat.descriptive	Generic univariate summary statistic objects.
org.apache.commons.math3.stat.descriptive.moment	Summary statistics based on moments.
org.apache.commons.math3.stat.descriptive.rank	Summary statistics based on ranks.
org.apache.commons.math3.stat.descriptive.summary	Other summary statistics.

Uses of UnivariateStatistic in org.apache.commons.math3.stat.descriptive

Subinterfaces of UnivariateStatistic in org.apache.commons.math3.stat.descriptive

Modifier and Type	Interface and Description
interface	StorelessUnivariateStatistic Extends the definition of UnivariateStatistic with StorelessUnivariateStatistic.increment(double) and StorelessUnivariateStatistic.incrementAll(double[]) methods for adding values and updating internal state.

Classes in org.apache.commons.math3.stat.descriptive that implement UnivariateStatistic

Modifier and Type	Class and Description
class	AbstractStorelessUnivariateStatistic Abstract implementation of the StorelessUnivariateStatistic interface.
class	AbstractUnivariateStatistic Abstract base class for all implementations of the UnivariateStatistic interface.

Methods in org.apache.commons.math3.stat.descriptive that return UnivariateStatistic

Modifier and Type	Method and Description
UnivariateStatistic	UnivariateStatistic.copy() Returns a copy of the statistic with the same internal state.
abstract UnivariateStatistic	AbstractUnivariateStatistic.copy() Returns a copy of the statistic with the same internal state.
UnivariateStatistic	DescriptiveStatistics.getGeometricMeanImpl() Returns the currently configured geometric mean implementation.
UnivariateStatistic	DescriptiveStatistics.getKurtosisImpl() Returns the currently configured kurtosis implementation.
UnivariateStatistic	DescriptiveStatistics.getMaxImpl() Returns the currently configured maximum implementation.
UnivariateStatistic	DescriptiveStatistics.getMeanImpl() Returns the currently configured mean implementation.
UnivariateStatistic	DescriptiveStatistics.getMinImpl() Returns the currently configured minimum implementation.
UnivariateStatistic	DescriptiveStatistics.getPercentileImpl() Returns the currently configured percentile implementation.
UnivariateStatistic	DescriptiveStatistics.getSkewnessImpl() Returns the currently configured skewness implementation.
UnivariateStatistic	DescriptiveStatistics.getSumImpl() Returns the currently configured sum implementation.
UnivariateStatistic	DescriptiveStatistics.getSumsqImpl() Returns the currently configured sum of squares implementation.
UnivariateStatistic	DescriptiveStatistics.getVarianceImpl() Returns the currently configured variance implementation.

Methods in org.apache.commons.math3.stat.descriptive with parameters of type UnivariateStatistic

Modifier and Type	Method and Description
double	SynchronizedDescriptiveStatistics.apply(UnivariateStatistic stat) Apply the given statistic to the data associated with this set of statistics.
double	DescriptiveStatistics.apply(UnivariateStatistic stat) Apply the given statistic to the data associated with this set of statistics.
void	DescriptiveStatistics.setGeometricMeanImpl(UnivariateStatistic geometricMeanImpl) Sets the implementation for the gemoetric mean.
void	DescriptiveStatistics.setKurtosisImpl(UnivariateStatistic kurtosisImpl) Sets the implementation for the kurtosis.
void	DescriptiveStatistics.setMaxImpl(UnivariateStatistic maxImpl) Sets the implementation for the maximum.
void	DescriptiveStatistics.setMeanImpl(UnivariateStatistic meanImpl) Sets the implementation for the mean.
void	DescriptiveStatistics.setMinImpl(UnivariateStatistic minImpl) Sets the implementation for the minimum.
void	DescriptiveStatistics.setPercentileImpl(UnivariateStatistic percentileImpl) Sets the implementation to be used by DescriptiveStatistics.getPercentile(double).
void	DescriptiveStatistics.setSkewnessImpl(UnivariateStatistic skewnessImpl) Sets the implementation for the skewness.
void	DescriptiveStatistics.setSumImpl(UnivariateStatistic sumImpl) Sets the implementation for the sum.
void	DescriptiveStatistics.setSumsqImpl(UnivariateStatistic sumsqImpl) Sets the implementation for the sum of squares.
void	DescriptiveStatistics.setVarianceImpl(UnivariateStatistic varianceImpl) Sets the implementation for the variance.

Uses of UnivariateStatistic in org.apache.commons.math3.stat.descriptive.moment

Classes in org.apache.commons.math3.stat.descriptive.moment that implement UnivariateStatistic

Modifier and Type	Class and Description
class	GeometricMean Returns the geometric mean of the available values.
class	Kurtosis Computes the Kurtosis of the available values.
class	Mean Computes the arithmetic mean of a set of values.
class	SecondMoment Computes a statistic related to the Second Central Moment.
class	SemiVariance Computes the semivariance of a set of values with respect to a given cutoff value.
class	Skewness Computes the skewness of the available values.
class	StandardDeviation Computes the sample standard deviation.
class	Variance Computes the variance of the available values.

Uses of UnivariateStatistic in org.apache.commons.math3.stat.descriptive.rank

Classes in org.apache.commons.math3.stat.descriptive.rank that implement UnivariateStatistic

Modifier and Type	Class and Description
class	Max Returns the maximum of the available values.
class	Median Returns the median of the available values.
class	Min Returns the minimum of the available values.
class	Percentile Provides percentile computation.
class	PSquarePercentile A StorelessUnivariateStatistic estimating percentiles using the P2 Algorithm as explained by Raj Jain and Imrich Chlamtac in P2 Algorithm for Dynamic Calculation of Quantiles and Histogram Without Storing Observations.

Uses of UnivariateStatistic in org.apache.commons.math3.stat.descriptive.summary

Classes in org.apache.commons.math3.stat.descriptive.summary that implement UnivariateStatistic

Modifier and Type	Class and Description
class	Product Returns the product of the available values.
class	Sum Returns the sum of the available values.
class	SumOfLogs Returns the sum of the natural logs for this collection of values.
class	SumOfSquares Returns the sum of the squares of the available values.