AbstractArrayDistance<T extends Number> 
Ancestor for distance measures.

AbstractArrayStatistic<T extends Serializable> 
Ancestor for classes that calculate statistics from arrays.

AbstractArrayStatistic.StatisticContainer<T extends Serializable> 
The container for the generated statistic result.

AbstractDataContainerStatistics<T extends DataContainer> 
Ancestor for all schemes that calculate statistics on data containers.

AbstractDataStatistic<T extends DataContainer> 
A class for statistics about data.

AbstractOptionalSampleArrayStatistic<T extends Serializable> 
Abstract super class for array statistics that can interprete the arrays
either as samples or populations.

ArrayAndrewsCurves<T extends Number> 
Generates Andrews Curves from array data.
César Ignacio García Osorio, Colin Fyfe (2003).

ArrayAngle<T extends Number> 
Calculates the angle between the first array and the remaining arrays.

ArrayBinning<T extends Number> 
Bins the data from given array using the specified algorithm and postprocessing approach.

ArrayChebyshevDistance 
Calculates the Chebyshev distance between the first array and the remaining arrays.

ArrayCorrelationCoefficient<T extends Number> 
Calculates the correlation coefficient between the first array and the remaining arrays.

ArrayCovariance<T extends Number> 
Calculates the covariance between the first array and the remaining arrays.

ArrayDifference<T extends Number> 
Calculates the difference between the arrays.

ArrayEuclideanDistance 
Calculates the Euclidean distance between the first array and the remaining arrays.

ArrayHistogram<T extends Number> 
Generates a histogram from the given array.
The formulas for the various width/#bin calculations can be found here:
WikiPedia (2010).

ArrayKendallTheil<T extends Number> 
Calculates the KendallTheil robust slope (also called TheilSen estimator) between the first array and the remaining arrays.

ArrayLength<T extends Serializable> 
Determines the length of an array.

ArrayLinearRegression<T extends Number> 
Calculates the slope and intercept of linear regression between two arrays (x and y).
If more than two arrays supplied, then the linear regression is computed between the first (x) and all the other ones (y).

ArrayManhattanDistance 
Calculates the Manhattan distance between the first array and the remaining arrays.

ArrayMax<T extends Number> 
Determines the max value in a numeric array.

ArrayMean<T extends Number> 
Calculates the mean for a numeric array.

ArrayMeanAbsoluteError<T extends Number> 
Calculates the mean absolute error (MAE) between the first array (actual) and the remaining arrays (predicted).

ArrayMedian<T extends Number> 
Calculates the median for a numeric array.

ArrayMin<T extends Number> 
Determines the min value in a numeric array.

ArrayMinkowskiDistance 
Calculates the Minkowski distance between the first array and the remaining arrays.

ArrayNormalize<T extends Number> 
Normalizes the array(s), i.e., the sum of its/their values is 1.0.

ArrayNormalizeRange<T extends Number> 
Normalizes the array(s) to the specified lower and upper bound.

ArrayPercentile<T extends Number> 
Determines the percentile for an array.

ArrayRelativeAbsoluteError<T extends Number> 
Calculates the relative absolute error (RAE) between the first array (actual) and the remaining arrays (predicted).

ArrayRootMeanSquaredError<T extends Number> 
Calculates the root mean squared error (RMSE) between the first array (actual) and the remaining arrays (predicted).

ArrayRootRelativeSquaredError<T extends Number> 
Calculates the root relative squared error (RRSE) between the first array (actual) and the remaining arrays (predicted).

ArrayRSquared<T extends Number> 
Calculates the R^2 between the first array and the remaining arrays.

ArrayStandardDeviation<T extends Number> 
Calculates the standard deviation for a numeric array.

ArrayStandardize<T extends Number> 
Standardizes the values in the array(s) to have mean 0 and stdev 1.

ArrayStandardScores<T extends Number> 
Calculates the standard scores (or z scores) of the provided arrays.The arrays must be numeric, of course.

ArraySum<T extends Number> 
Determines the sum of all values in a numeric array.

MultiArrayStatistic<T extends Number> 
Merges the spreadsheets generated by its substatistics into a single one.

Percentile<E extends Comparable> 
Container class for sortable values, which allows to extract percentiles
and percentiles.

SPCUtils 
Helper class for statistical process control (SPC).

SpectralAngleMapperUtils 
Utility class for performing spectral angle mapping between spectra.

StatCalc 

StatUtils 
A statistical helper class.

TimeseriesStatistic<T extends Timeseries> 
Statistical information specific to a Timeseries.
