Assembly: Extreme.Numerics (Extreme.Numerics)
Syntax
| Visual Basic (Declaration) |
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Public MustInherit Class AnovaModel _ Inherits GeneralLinearModel |
| C# |
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public abstract class AnovaModel : GeneralLinearModel |
| C++ |
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public ref class AnovaModel abstract : public GeneralLinearModel |
Methods
| Icon | Type | Description |
|---|---|---|
 | Compute() |
Computes the model.
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 | ComputeModel() |
Implemented by inheritors to perform the model calculations.
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| Contains(GeneralLinearModel) |
Returns a value that indicates whether another GeneralLinearModel is nested
within this instance.
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| Equals(Object) | |
| Finalize() | |
| GetFactor(Int32) |
Gets the factor corresponding to the variable with the specified index.
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| GetFactor(String) |
Gets the factor corresponding to the variable with the specified name.
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| GetHashCode() | Serves as a hash function for a particular type. |
| GetHomogeneityOfVariancesTest() |
Returns a test to verify that the cells have the same variance.
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| GetHomogeneityOfVariancesTest(TestOfHomogeneityOfVariances) |
Returns a test to verify that the cells have the same variance.
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| GetType() | Gets the Type of the current instance. |
| MemberwiseClone() | Creates a shallow copy of the current Object. |
| ResetComputation() |
Clears all computed model parameters.
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| SetAnovaModelRow(Int32, String, Double, Double) |
Sets the data of a row in the model's AnovaTable.
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| SetAnovaRow(AnovaRowType, String, Double, Double) |
Sets the data of a row in the model's AnovaTable.
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| ToString() |
Returns a string representation of this instance.
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Constructors
| Icon | Type | Description |
|---|---|---|
| AnovaModelNew(Int32, DataTable, String, String[]()) |
Constructs a new AnovaModel objects.
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| AnovaModelNew(VariableCollection, String, String[]()) |
Constructs a new AnovaModel objects.
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| AnovaModelNew(NumericalVariable, Variable[]()) |
Constructs a new AnovaModel objects.
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Properties
| Icon | Type | Description |
|---|---|---|
 | AdjustedRSquared |
Gets the adjusted R Squared value for the regression.
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| AnovaTable |
Gets the AnovaTable that summarizes the results of this model.
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| Cells |
Gets the collection of data cells for this model.
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| Computed |
Gets a value that indicates whether the regression model has been computed.
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| DegreesOfFreedom |
Gets the total degrees of freedom of the data.
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| DependentVariables |
Gets the collection of dependent variables associated with this model.
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| FStatistic |
Gets the F statistic for the regression.
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| IndependentVariables |
Gets the collection of independent variables associated with this model.
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| IsBalanced |
Gets a value that indicates whether this ANOVA design is balanced.
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| Parameters |
Gets the collection of parameters associated with this model.
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| PValue |
Gets the probability corresponding to the F statistic for the regression.
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| ResidualSumOfSquares |
Gets the sum of squares of the residuals of the model.
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| RSquared |
Gets the R Squared value for the regression.
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| StandardError |
Gets the standard error of the regression.
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Remarks
The AnovaModel class is an abstract base class for all classes that implement Analysis of Variance (ANOVA) models. It inherits from GeneralLinearModel, and defines a number of additional properties and methods useful in analysis of variance.
ANOVA models are a specialized form of GeneralLinearModel whose independent variables or predictors are all categorical in nature. The categorical scales are called factors. Use the GetFactor(Int32) method to get the factor that corresponds to a specific independent variable.
The Cells property returns a CellArray object that represents the data organized into cells. There is one cell for every combination of factor levels. The IsBalanced property indicates whether all cells have the same number of observations.
One of the assumptions in analysis of variance is that the variances of the data in each cell are the same. The GetHomogeneityOfVariancesTest() returns a hypothesis test object that allows you to verify this assumption.
This is an abstract base class, and cannot be instantiated directly. Instead, use one of the derived classes listed in the following table. ClassDescriptionOneWayAnovaModelRepresents a one-way analysis of variance model.OneWayRAnovaModelRepresents a one-way analysis of variance model with repeated measures.TwoWayAnovaModelRepresents a two-way analysis of variance.
Inheritance Hierarchy
