Uses of Class
de.lmu.ifi.dbs.elki.math.MeanVariance

Packages that use MeanVariance

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan	Generalized DBSCAN Generalized DBSCAN is an abstraction of the original DBSCAN idea, that allows the use of arbitrary "neighborhood" and "core point" predicates.
de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased	Angle-based outlier detection algorithms.
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise	Normalizations operating on columns / variates; where each column is treated independently.
de.lmu.ifi.dbs.elki.evaluation.clustering	Evaluation of clustering results
de.lmu.ifi.dbs.elki.math	Mathematical operations and utilities used throughout the framework
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator	Estimators for statistical distributions.
de.lmu.ifi.dbs.elki.math.statistics.tests	Statistical tests

Uses of MeanVariance in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan declared as MeanVariance

Modifier and Type	Field and Description
private MeanVariance	FourCNeighborPredicate.mvCorDim Tool to help with parameterization.
private MeanVariance	PreDeConNeighborPredicate.mvSize Tool to help with parameterization.
private MeanVariance	FourCNeighborPredicate.mvSize Tool to help with parameterization.
private MeanVariance	FourCNeighborPredicate.mvSize2 Tool to help with parameterization.
private MeanVariance	PreDeConNeighborPredicate.mvVar Tool to help with parameterization.

Uses of MeanVariance in de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased with parameters of type MeanVariance

Modifier and Type	Method and Description
protected double	ABOD.computeABOF(KernelMatrix kernelMatrix, DBIDRef pA, DBIDArrayIter pB, DBIDArrayIter pC, MeanVariance s) Compute the exact ABOF value.

Uses of MeanVariance in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise

Fields in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise declared as MeanVariance

Modifier and Type	Field and Description
(package private) MeanVariance[]	AttributeWiseVarianceNormalization.mvs Temporary storage used during initialization.

Uses of MeanVariance in de.lmu.ifi.dbs.elki.evaluation.clustering

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering that return MeanVariance

Modifier and Type	Method and Description
MeanVariance	ClusterContingencyTable.averageSymmetricGini() Compute the average Gini for each cluster (in both clusterings - symmetric).

Uses of MeanVariance in de.lmu.ifi.dbs.elki.math

Subclasses of MeanVariance in de.lmu.ifi.dbs.elki.math

Modifier and Type	Class and Description
class	MeanVarianceMinMax Class collecting mean, variance, minimum and maximum statistics.
class	StatisticalMoments Track various statistical moments, including mean, variance, skewness and kurtosis.

Methods in de.lmu.ifi.dbs.elki.math that return MeanVariance

Modifier and Type	Method and Description
static MeanVariance[]	MeanVariance.newArray(int dimensionality) Create and initialize a new array of MeanVariance
MeanVariance	MeanVariance.put(double[] vals) Add values with weight 1.0
MeanVariance	MeanVarianceMinMax.put(double[] vals, double[] weights)
MeanVariance	MeanVariance.put(double[] vals, double[] weights)

Constructors in de.lmu.ifi.dbs.elki.math with parameters of type MeanVariance

Constructor and Description
MeanVariance(MeanVariance other) Constructor from other instance

Uses of MeanVariance in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Methods in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator with parameters of type MeanVariance

Modifier and Type	Method and Description
ExpGammaDistribution	ExpGammaExpMOMEstimator.estimateFromExpMeanVariance(MeanVariance mv)
D	LogMeanVarianceEstimator.estimateFromLogMeanVariance(MeanVariance mv, double shift) Estimate the distribution from mean and variance.
LogNormalDistribution	LogNormalLogMOMEstimator.estimateFromLogMeanVariance(MeanVariance mv, double shift)
InverseGaussianDistribution	InverseGaussianMOMEstimator.estimateFromMeanVariance(MeanVariance mv)
ExponentialDistribution	ExponentialMOMEstimator.estimateFromMeanVariance(MeanVariance mv)
D	MeanVarianceDistributionEstimator.estimateFromMeanVariance(MeanVariance mv) Estimate the distribution from mean and variance.
NormalDistribution	NormalMOMEstimator.estimateFromMeanVariance(MeanVariance mv)
GammaDistribution	GammaMOMEstimator.estimateFromMeanVariance(MeanVariance mv)

Uses of MeanVariance in de.lmu.ifi.dbs.elki.math.statistics.tests

Methods in de.lmu.ifi.dbs.elki.math.statistics.tests with parameters of type MeanVariance

Modifier and Type	Method and Description
static int	WelchTTest.calculateDOF(MeanVariance mv1, MeanVariance mv2) Calculates the degree of freedom according to Welch-Satterthwaite
static double	WelchTTest.calculateTestStatistic(MeanVariance mv1, MeanVariance mv2) Calculate the statistic of Welch's t test using statistical moments of the provided data samples