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• Extreme.Statistics
  • AnovaModel Class
  • AnovaModelRow Class
  • AnovaRow Class
  • AnovaRowType Enumeration
  • AnovaTable Class
  • Cell Structure
  • ContingencyTable Class
  • ContingencyTableCell Structure
  • DateTimeInterval Structure
  • Descriptives(T) Class
  • Filter Class
  • GeneralizedLinearModel Class
  • HypothesisTests Class
  • Kernel Class
  • KernelDensity Class
  • KernelDensityBandwidthEstimator Enumeration
  • LinearRegressionModel Class
  • LinkFunction Class
  • LogisticRegressionMethod Enumeration
  • LogisticRegressionModel Class
  • ModelFamily Class
  • NearestCorrelationMatrixAlgorithm Enumeration
  • NonlinearRegressionModel Class
  • OneWayAnovaModel Class
  • OneWayRAnovaModel Class
  • PolynomialRegressionModel Class
  • RegularizedRegressionModel Class
  • ScaleFittingMethod Enumeration
  • SimpleRegressionKind Enumeration
  • SimpleRegressionModel Class
  • Stats Class
  • StepwiseCriterion Enumeration
  • StepwiseOptions Class
  • StepwiseRegressionMethod Enumeration
  • SumsOfSquaresType Enumeration
  • TestOfHomogeneityOfVariances Enumeration
  • TestOfNormality Enumeration
  • TwoWayAnovaModel Class
  • WindowFilter Class

Extreme.Statistics Namespace

Extreme Optimization Numerical Libraries for .NET Professional

The Extreme.Statistics namespace contains classes that are used to represent statistical models.

Classes

---

	Class	Description
	AnovaModel	Represents an Analysis of Variance (ANOVA) model.
	AnovaModelRow	Represents a row representing a contribution from the model in an AnovaTable.
	AnovaRow	Represents a row in an AnovaTable.
	AnovaTable	Represents a table containing the results of an ANOVA analysis.
	ContingencyTable	Represents a table that cross-tabulates totals from two categorical variables.
	DescriptivesT	Collects descriptive statistics for a variable.
	Filter	Represents a filter that can be used to select observations in a VectorT or IDataFrame.
	GeneralizedLinearModel	Represents a generalized linear model.
	HypothesisTests	Contains static methods to create hypothesis tests.
	Kernel	Represents a kernel used for kernel density estimation.
	KernelDensity	Contains methods for computing kernel density estimates.
	LinearRegressionModel	Represents a linear regression model.
	LinkFunction	Represents a link function in a GeneralizedLinearModel.
	LogisticRegressionModel	Represents a logistic regression model.
	ModelFamily	Represents a family of distributions for the dependent variable in a GeneralizedLinearModel.
	NonlinearRegressionModel	Represents a nonlinear regression model.
	OneWayAnovaModel	Represents the results of a one-way analysis of variance (ANOVA).
	OneWayRAnovaModel	Represents an analysis of variance (ANOVA) calculation.
	PolynomialRegressionModel	Represents a polynomial regression model.
	RegularizedRegressionModel	Represents a regularized (ridge or LASSO) regression model.
	SimpleRegressionModel	Represents a linear regression model.
	Stats	Provides static methods for descriptive statistics and other statistical functions.
	StepwiseOptions	Specifies options for stepwise regression calculations.
	TwoWayAnovaModel	Represents a two-way within-subjects Analysis of Variance (ANOVA) model.
	WindowFilter	Represents a sliding window on a variable or variable collection.

Structures

---

	Structure	Description
	Cell	Represents a data cell in an AnovaModel.
	ContingencyTableCell	Represents a bin in a ContingencyTable.
	DateTimeInterval	Represents an interval of real numbers.

Enumerations

---

	Enumeration	Description
	AnovaRowType	Enumerates the possible types of rows in an AnovaTable.
	KernelDensityBandwidthEstimator	Enumerates the options for estimating the bandwidth in kernel density estimation.
	LogisticRegressionMethod	Enumerates the variants of logistic regression that can be represented by a LogisticRegressionModel.
	NearestCorrelationMatrixAlgorithm	Enumerates the possible algorithms for computing the nearest correlation matrix.
	ScaleFittingMethod	Enumerates the possible ways to estimate the scale parameter in a generalized linear model.
	SimpleRegressionKind	Enumerates the different kinds of regression between two variables.
	StepwiseCriterion	Enumerates the possible ways to define the threshold for the to-enter and to-remove values.
	StepwiseRegressionMethod	Enumerates the possible ways to perform a stepwise regression.
	SumsOfSquaresType	Enumerates the types of sums of squares available when computing an ANOVA table.
	TestOfHomogeneityOfVariances	Enumerates the choices when testing whether a number of samples have the same variance.
	TestOfNormality	Enumerates the choices when testing whether a sample follows a normal distribution.

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