All Classes and Interfaces

Class	Description
AbstractMultipleLinearRegression	Abstract base class for implementations of MultipleLinearRegression.
AbstractStorelessUnivariateStatistic	Abstract base class for implementations of the StorelessUnivariateStatistic interface.
AbstractUnivariateStatistic	Abstract base class for implementations of the UnivariateStatistic interface.
AggregatableStatistic<T>	An interface for statistics that can aggregate results.
AlternativeHypothesis	Represents an alternative hypothesis for a hypothesis test.
BinomialProportion	Utility methods to generate confidence intervals for a binomial proportion.
BinomialTest	Implements binomial test statistics.
ChiSquareTest	Implements Chi-Square test statistics.
ConfidenceInterval	Represents an interval estimate of a population parameter.
Covariance	Computes covariances for pairs of arrays or columns of a matrix.
DescriptiveStatistics	Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data.
EmpiricalDistribution	Represents an empirical probability distribution -- a probability distribution derived from observed data without making any assumptions about the functional form of the population distribution that the data come from.
Frequency<T extends Comparable<T>>	Maintains a frequency distribution of Comparable values.
GeometricMean	Returns the geometric mean of the available values.
GLSMultipleLinearRegression	The GLS implementation of multiple linear regression.
GTest	Implements G Test statistics.
InferenceTestUtils	A collection of static methods to create inference test instances or to perform inference tests.
KendallsCorrelation	Implementation of Kendall's Tau-b rank correlation.
KolmogorovSmirnovTest	Implementation of the Kolmogorov-Smirnov (K-S) test for equality of continuous distributions.
Kurtosis	Computes the Kurtosis of the available values.
LocalizedStatFormats	Enumeration for localized messages formats used in exceptions messages.
LongFrequency	Maintains a frequency distribution of Long values.
MannWhitneyUTest	An implementation of the Mann-Whitney U test.
Max	Returns the maximum of the available values.
Mean	Computes the arithmetic mean of a set of values.
Median	Returns the median of the available values.
MillerUpdatingRegression	This class is a concrete implementation of the UpdatingMultipleLinearRegression interface.
Min	Returns the minimum of the available values.
MultipleLinearRegression	The multiple linear regression can be represented in matrix-notation.
MultivariateNormalMixtureExpectationMaximization	Expectation-Maximization algorithm for fitting the parameters of multivariate normal mixture model distributions.
MultivariateSummaryStatistics	Computes summary statistics for a stream of n-tuples added using the addValue method.
NaNStrategy	Strategies for handling NaN values in rank transformations.
NaturalRanking	Ranking based on the natural ordering on doubles.
OLSMultipleLinearRegression	Implements ordinary least squares (OLS) to estimate the parameters of a multiple linear regression model.
OneWayAnova	Implements one-way ANOVA (analysis of variance) statistics.
PCA	Principal component analysis (PCA) is a statistical technique for reducing the dimensionality of a dataset.
PearsonsCorrelation	Computes Pearson's product-moment correlation coefficients for pairs of arrays or columns of a matrix.
Percentile	Provides percentile computation.
Percentile.EstimationType	An enum for various estimation strategies of a percentile referred in wikipedia on quantile with the names of enum matching those of types mentioned in wikipedia.
Product	Returns the product of the available values.
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.
PSquarePercentile.PSquareMarkers	An interface that encapsulates abstractions of the P-square algorithm markers as is explained in the original works.
RandomPercentile	A StorelessUnivariateStatistic estimating percentiles using the RANDOM Algorithm.
RankingAlgorithm	Interface representing a rank transformation.
RegressionResults	Results of a Multiple Linear Regression model fit.
SecondMoment	Computes a statistic related to the Second Central Moment.
SemiVariance	Computes the semivariance of a set of values with respect to a given cutoff value.
SemiVariance.Direction	The direction of the semivariance - either upside or downside.
SimpleRegression	Estimates an ordinary least squares regression model with one independent variable.
Skewness	Computes the skewness of the available values.
SpearmansCorrelation	Spearman's rank correlation.
StandardDeviation	Computes the sample standard deviation.
StatisticalMultivariateSummary	Reporting interface for basic multivariate statistics.
StatisticalSummary	Reporting interface for basic univariate statistics.
StatisticalSummaryValues	Value object representing the results of a univariate statistical summary.
StatUtils	StatUtils provides static methods for computing statistics based on data stored in double[] arrays.
StorelessCovariance	Covariance implementation that does not require input data to be stored in memory.
StorelessMultivariateStatistic	Base interface implemented by storeless multivariate statistics.
StorelessUnivariateStatistic	Extends the definition of UnivariateStatistic with StorelessUnivariateStatistic.increment(double) and StorelessUnivariateStatistic.incrementAll(double[]) methods for adding values and updating internal state.
StreamingStatistics	Computes summary statistics for a stream of data values added using the addValue method.
StreamingStatistics.StreamingStatisticsBuilder	Builder for StreamingStatistics instances.
Sum	Returns the sum of the available values.
SumOfLogs	Returns the sum of the natural logs for this collection of values.
SumOfSquares	Returns the sum of the squares of the available values.
TiesStrategy	Strategies for handling tied values in rank transformations.
TTest	An implementation for Student's t-tests.
UnivariateStatistic	Base interface implemented by all statistics.
UpdatingMultipleLinearRegression	An interface for regression models allowing for dynamic updating of the data.
Variance	Computes the variance of the available values.
VectorialCovariance	Returns the covariance matrix of the available vectors.
VectorialStorelessStatistic	Uses an independent StorelessUnivariateStatistic instance for each component of a vector.
WeightedEvaluation	Weighted evaluation for statistics.
WilcoxonSignedRankTest	An implementation of the Wilcoxon signed-rank test.