| 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 null-hypothesis 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 multiple-hypothesis comparison algorithm based on making multiple
pair-wise null-hypothesis comparisons.
|
| AbstractPairwiseMultipleHypothesisComparison.Statistic
Result from a pairwise multiple-comparison statistic.
|
| AdjustedPValueStatistic
A multiple-comparison statistic derived from a single adjusted p-value.
|
| AnalysisOfVarianceOneWay
Analysis of Variance single-factor null-hypothesis testing procedure,
usually called "1-way 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 null-hypothesis multiple-comparison test from a block-design
experiment.
|
| BonferroniCorrection
The Bonferroni correction takes a pair-wise null-hypothesis test and
generalizes it to multiple comparisons by adjusting the requisite p-value
to find significance as alpha / NumComparisons.
|
| ChebyshevInequality
Computes the Chebyshev Inequality for the given level of confidence.
|
| ChiSquareConfidence
This is the chi-square goodness-of-fit test.
|
| ChiSquareConfidence.Statistic
Confidence Statistic for a chi-square 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 null-hypothesis 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
F-statistic.
|
| 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 pair-wide p-values and then adjusting the
p-values by the number of remaining hypotheses.
|
| HolmCorrection.Statistic
Test statistic from the Shaffer static multiple-comparison test
|
| KolmogorovSmirnovConfidence
Performs a Kolmogorov-Smirnov Confidence Test.
|
| KolmogorovSmirnovConfidence.Statistic
Computes the ConfidenceStatistic associated with a K-S test
|
| MannWhitneyUConfidence.Statistic
Statistics from the Mann-Whitney U-test
|
| MarkovInequality
Implementation of the Markov Inequality hypothesis test.
|
| MaximumLikelihoodDistributionEstimator
Estimates the most-likely distribution, and corresponding parameters, of
that generated the given data from a pre-determined collection of
candidate parameteric distributions.
|
| MultipleComparisonExperiment
A multiple comparisons experiment that does a block comparison and then a
post-hoc 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 rank-based analogue of the Tukey multiple-comparison
test.
|
| NemenyiConfidence.Statistic
Statistic from Nemenyi's multiple comparison test
|
| NullHypothesisEvaluator
Evaluates the probability that the null-hypothesis 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 multiple-comparison test
|
| SidakCorrection
The Sidak correction takes a pair-wise null-hypothesis test and
generalizes it to multiple comparisons by adjusting the requisite p-value
to find significance as alpha / NumComparisons.
|
| StudentTConfidence
This class implements Student's t-tests for different uses.
|
| StudentTConfidence.Statistic
Confidence statistics for a Student-t test
|
| TukeyKramerConfidence
Tukey-Kramer test is the multiple-comparison generalization of the unpaired
Student's t-test when conducting multiple comparisons.
|
| TukeyKramerConfidence.Statistic
Statistic from Tukey-Kramer's multiple comparison test
|
| WilcoxonSignedRankConfidence
This is a Wilcoxon Signed-Rank Sum test, which performs a pair-wise test
to determine if two datasets are different.
|
| WilcoxonSignedRankConfidence.Statistic
ConfidenceStatistics associated with a Wilcoxon test
|