Home > Extreme Optimization Statistics Library for .NET > Reference >
The Extreme.Statistics namespace contains classes that are used to represent statistical models.
| Class | Description |
|---|---|
| Aggregator | Represents a method that aggregates data in a variable. |
| 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. |
| AnovaRowCollection | Represents a collection of AnovaRow objects. |
| AnovaTable | Represents a table containing the results of an ANOVA analysis. |
| CategoricalScale | Represents a discrete classification of a Variable. |
| CategoricalVariable | Represents a statistical Variable that can take on a discrete set of values. |
| Cell | Represents a data cell in an AnovaModel. |
| CellArray | Represents the summary data in the cells of an ANOVA table. |
| DataArrayBase | Represents a multidimensional data store. |
| DataArrayElement | Represents an element in a DataArrayBase. |
| DateTimeScale | Represents a mapping from DateTime values to a discrete scale of time periods. |
| DateTimeVariable | Represents a statistical variable that takes on date/time values. |
| GeneralLinearModel | Represents a statistical model. |
| Histogram | Represents a histogram. |
| HistogramBin | Represents a bin in a Histogram. |
| InsufficientDataException | Represents an exception that may be thrown when a variable or variable collection contains insufficient data to perform a calculation. |
| KeyVariable | Represents a variable containing row keys. |
| License | Used to verify this copy of the Extreme Optimization Statistics Library for .NET is properly licensed. |
| LicenseProvider | |
| LinearRegressionModel | Represents a linear regression model. |
| MissingValueException | Represents an exception that may be thrown when a missing data value is encountered during a calculation. |
| NumericalScale | Represents a division of a numerical range into a number of intervals. |
| NumericalVariable | Represents a statistical variable that takes on numerical values. |
| OneWayAnovaModel | Represents the results of a one-way analysis of variance (ANOVA). |
| OneWayRAnovaModel | Represents an analysis of variance (ANOVA) calculation. |
| Parameter | Represents a parameter in a statistical model. |
| ParameterCollection | Represents a collection of Parameter objects. |
| PolynomialRegressionModel | Represents a polynomial regression model. |
| SimpleRegressionModel | Represents a linear regression model. |
| Stats | Provides static methods for descriptive statistics and other statistical functions. |
| TwoWayAnovaModel | Represents a two-way within-subjects Analysis of Variance (ANOVA) model. |
| Variable | Represents a statistical variable. |
| VariableCollection | Represents a collection of variables in a statistical model. |
| Structure | Description |
|---|---|
| DateTimeInterval | Represents an interval of real numbers. |
| HistogramBinCollection | Represents a collection of bins in a Histogram. |
| Interval | Represents an interval of real numbers. |
| NumericalVariableTransforms | Represents transformations that can be applied to a numerical variable. |
| ObservationRow | |
| ObservationRowCollection |
| Enumeration | Description |
|---|---|
| AnovaRowType | Enumerates the possible types of rows in an AnovaTable. |
| BoundaryIntervalBehavior | Enumerates how segments at the boundaries of subdivided series are handled. |
| DateTimeUnit | Enumerates the time units. |
| MissingValueAction | Enumerates the possible actions to be taken when a calculation encounters a missing value. |
| SortOrder | Enumerates the ways data can be sorted. |
| SpecialBins | Enumerates the possible special bins to be included in a CategoricalScale. |
| 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. |
| VariableUsage | Enumerates the way variables may be used in a GeneralLinearModel. |