Package  Description 

gov.sandia.cognition.learning.algorithm.regression 
Provides regression algorithms, such as Linear Regression.

gov.sandia.cognition.learning.experiment 
Provides experiments for validating the performance of learning algorithms.

gov.sandia.cognition.learning.performance.categorization 
Provides performance measures for categorizers.

gov.sandia.cognition.statistics 
Provides the inheritance hierarchy for general statistical methods and distributions.

gov.sandia.cognition.statistics.bayesian 
Provides algorithms for computing Bayesian estimates of parameters.

gov.sandia.cognition.statistics.distribution 
Provides statistical distributions.

gov.sandia.cognition.statistics.method 
Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.

Class and Description 

AbstractConfidenceStatistic
Abstract implementation of ConfidenceStatistic.

ConfidenceStatistic
An interface that describes the result of a statistical confidence test.

Class and Description 

ConfidenceStatistic
An interface that describes the result of a statistical confidence test.

NullHypothesisEvaluator
Evaluates the probability that the nullhypothesis is correct.

Class and Description 

ConfidenceInterval
Contains a specification for a confidence interval, that is, the solution of
Pr{ lowerBound <= x(centralValue) <= upperBound } >= confidence

Class and Description 

ConfidenceInterval
Contains a specification for a confidence interval, that is, the solution of
Pr{ lowerBound <= x(centralValue) <= upperBound } >= confidence

Class and Description 

ConfidenceInterval
Contains a specification for a confidence interval, that is, the solution of
Pr{ lowerBound <= x(centralValue) <= upperBound } >= confidence

Class and Description 

TreeSetBinner
Implements a
Binner that employs a TreeSet to define the
boundaries of a contiguous set of bins. 
Class and Description 

AbstractConfidenceStatistic
Abstract implementation of ConfidenceStatistic.

AbstractMultipleHypothesisComparison
Partial implementation of MultipleHypothesisComparison

AbstractMultipleHypothesisComparison.Statistic
Partial implementation of MultipleHypothesisComparison.Statistic

AbstractPairwiseMultipleHypothesisComparison
A multiplehypothesis comparison algorithm based on making multiple
pairwise nullhypothesis comparisons.

AbstractPairwiseMultipleHypothesisComparison.Statistic
Result from a pairwise multiplecomparison statistic.

AdjustedPValueStatistic
A multiplecomparison statistic derived from a single adjusted pvalue.

AnalysisOfVarianceOneWay
Analysis of Variance singlefactor nullhypothesis testing procedure,
usually called "1way ANOVA".

AnalysisOfVarianceOneWay.Statistic
Returns the confidence statistic for an ANOVA test

BernoulliConfidence
Computes the Bernoulli confidence interval.

Binner
Defines the functionality for a class that assigns values to some sort of
bin.

BlockExperimentComparison
Implements a nullhypothesis multiplecomparison test from a blockdesign
experiment.

BonferroniCorrection
The Bonferroni correction takes a pairwise nullhypothesis test and
generalizes it to multiple comparisons by adjusting the requisite pvalue
to find significance as alpha / NumComparisons.

ChebyshevInequality
Computes the Chebyshev Inequality for the given level of confidence.

ChiSquareConfidence
This is the chisquare goodnessoffit test.

ChiSquareConfidence.Statistic
Confidence Statistic for a chisquare test

ConfidenceInterval
Contains a specification for a confidence interval, that is, the solution of
Pr{ lowerBound <= x(centralValue) <= upperBound } >= confidence

ConfidenceIntervalEvaluator
Computes a confidence interval for a given dataset and confidence (power)
level

ConfidenceStatistic
An interface that describes the result of a statistical confidence test.

ConfidenceTestAssumptions
Describes the assumptions and other information of a statistical confidence
test.

ConvexReceiverOperatingCharacteristic
Computes the convex hull of the Receiver Operating Characteristic (ROC),
which a mathematician might call a "concave down" function.

DistributionParameterEstimator
A method of estimating the parameters of a distribution using an arbitrary
CostFunction and FunctionMinimizer algorithm.

DistributionParameterEstimator.DistributionWrapper
Maps the parameters of a Distribution and a CostFunction into a
Vector/Double Evaluator.

FieldConfidenceInterval
This class has methods that automatically compute confidence intervals for
Double/double Fields in dataclasses.

FisherSignConfidence.Statistic
Contains the parameters from the Sign Test nullhypothesis evaluation

FriedmanConfidence
The Friedman test determines if the rankings associated with various
treatments are equal.

FriedmanConfidence.Statistic
Confidence statistic associated with the Friedman test using the tighter
Fstatistic.

GaussianConfidence
This test is sometimes called the "Z test"
Defines a range of values that the statistic can take, as well as the
confidence that the statistic is between the lower and upper bounds.

GaussianConfidence.Statistic
Confidence statistics for a Gaussian distribution

HolmCorrection
The Holm correction is a uniformly tighter bound than the Bonferroni/Sidak
correction by first sorting the pairwide pvalues and then adjusting the
pvalues by the number of remaining hypotheses.

HolmCorrection.Statistic
Test statistic from the Shaffer static multiplecomparison test

KolmogorovSmirnovConfidence
Performs a KolmogorovSmirnov Confidence Test.

KolmogorovSmirnovConfidence.Statistic
Computes the ConfidenceStatistic associated with a KS test

MannWhitneyUConfidence.Statistic
Statistics from the MannWhitney Utest

MarkovInequality
Implementation of the Markov Inequality hypothesis test.

MaximumLikelihoodDistributionEstimator
Estimates the mostlikely distribution, and corresponding parameters, of
that generated the given data from a predetermined collection of
candidate parameteric distributions.

MultipleComparisonExperiment
A multiple comparisons experiment that does a block comparison and then a
posthoc test.

MultipleComparisonExperiment.Statistic
Result of running the MultipleHypothesisComparison hypothesis test

MultipleHypothesisComparison
Describes the functionality of an algorithm for accepting or rejecting
multiple null hypothesis at the same time.

MultipleHypothesisComparison.Statistic
Statistic associated with the multiple hypothesis comparison

NemenyiConfidence
The Nemenyi test is the rankbased analogue of the Tukey multiplecomparison
test.

NemenyiConfidence.Statistic
Statistic from Nemenyi's multiple comparison test

NullHypothesisEvaluator
Evaluates the probability that the nullhypothesis is correct.

ReceiverOperatingCharacteristic
Class that describes a Receiver Operating Characteristic (usually called an
"ROC Curve").

ReceiverOperatingCharacteristic.DataPoint
Contains information about a datapoint on an ROC curve

ReceiverOperatingCharacteristic.Statistic
Contains useful statistics derived from a ROC curve

ShafferStaticCorrection
The Shaffer Static Correction uses logical relationships to tighten up the
Bonferroni/Sidak corrections when performing pairwise multiple hypothesis
comparisons.

ShafferStaticCorrection.Statistic
Test statistic from the Shaffer static multiplecomparison test

SidakCorrection
The Sidak correction takes a pairwise nullhypothesis test and
generalizes it to multiple comparisons by adjusting the requisite pvalue
to find significance as alpha / NumComparisons.

StudentTConfidence
This class implements Student's ttests for different uses.

StudentTConfidence.Statistic
Confidence statistics for a Studentt test

TukeyKramerConfidence
TukeyKramer test is the multiplecomparison generalization of the unpaired
Student's ttest when conducting multiple comparisons.

TukeyKramerConfidence.Statistic
Statistic from TukeyKramer's multiple comparison test

WilcoxonSignedRankConfidence
This is a Wilcoxon SignedRank Sum test, which performs a pairwise test
to determine if two datasets are different.

WilcoxonSignedRankConfidence.Statistic
ConfidenceStatistics associated with a Wilcoxon test
