Numerics. NET. Statistics Namespace
The Numerics.NET.Statistics namespace contains classes that are used to represent statistical models.
Classes
Anova | Represents an Analysis of Variance (ANOVA) model. |
Anova | Represents a row representing a contribution from the model in an AnovaTable. |
Anova | Represents a row in an AnovaTable. |
Anova | Represents a table containing the results of an ANOVA analysis. |
Contingency | Represents a table that cross-tabulates totals from two categorical variables. |
Descriptives<T> | Collects descriptive statistics for a variable. |
Filter | Represents a filter that can be used to select observations in a Vector<T> or IDataFrame. |
Generalized | Represents a generalized linear model. |
Hypothesis | Contains static methods to create hypothesis tests. |
Kernel | Represents a kernel used for kernel density estimation. |
Kernel | Contains methods for computing kernel density estimates. |
Linear | Represents a linear regression model. |
Link | Represents a link function in a GeneralizedLinearModel. |
Logistic | Represents a logistic regression model. |
Model | Represents a family of distributions for the dependent variable in a GeneralizedLinearModel. |
Nonlinear | Represents a nonlinear regression model. |
One | Represents the results of a one-way analysis of variance (ANOVA). |
One | Represents an analysis of variance (ANOVA) calculation. |
Polynomial | Represents a polynomial regression model. |
Regression | Represents information about a step in a stepwise regression. |
Regularized | Represents a regularized (ridge or LASSO) regression model. |
Simple | Represents a linear regression model. |
Stats | Provides static methods for descriptive statistics and other statistical functions. |
Stepwise | Specifies options for stepwise regression calculations. |
Two | Represents a two-way within-subjects Analysis of Variance (ANOVA) model. |
Window | Represents a sliding window on a variable or variable collection. |
Structures
Cell | Represents a data cell in an AnovaModel. |
Contingency | Represents a bin in a ContingencyTable. |
Date | Represents an interval of real numbers. |
Enumerations
Anova | Enumerates the possible types of rows in an AnovaTable. |
Kernel | Enumerates the options for estimating the bandwidth in kernel density estimation. |
Logistic | Enumerates the variants of logistic regression that can be represented by a LogisticRegressionModel. |
Nearest | Enumerates the possible algorithms for computing the nearest correlation matrix. |
Regression | Enumerates the operations that may be performed during a single step in stepwise regression. |
Scale | Enumerates the possible ways to estimate the scale parameter in a generalized linear model. |
Simple | Enumerates the different kinds of regression between two variables. |
Stepwise | Enumerates the possible ways to define the threshold for the to-enter and to-remove values. |
Stepwise | Enumerates the possible ways to perform a stepwise regression. |
Sums | Enumerates the types of sums of squares available when computing an ANOVA table. |
Test | Enumerates the choices when testing whether a number of samples have the same variance. |
Test | Enumerates the choices when testing whether a sample follows a normal distribution. |