Double |
DoubleFactorAnalysis
[SerializableAttribute] public class DoubleFactorAnalysis<Extraction, Rotation> : ICloneable where Extraction : new(), IFactorExtraction where Rotation : new(), IFactorRotation
IFactorExtraction
IFactorRotation
The DoubleFactorAnalysisExtraction, Rotation type exposes the following members.
Name | Description | |
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DoubleFactorAnalysisExtraction, Rotation(DoubleFactorAnalysisExtraction, Rotation) | Copy constructor. Initializes self with the state of other. | |
DoubleFactorAnalysisExtraction, Rotation(DoubleSymmetricMatrix) |
Constructs a C# DoubleFactorAnalysis C# Extraction C# Rotation | |
DoubleFactorAnalysisExtraction, Rotation(DoubleSymmetricMatrix, Extraction) |
Constructs a C# DoubleFactorAnalysis C# Rotation | |
DoubleFactorAnalysisExtraction, Rotation(DoubleSymmetricMatrix, BiasType) |
Constructs a C# DoubleFactorAnalysis C# Extraction C# Rotation | |
DoubleFactorAnalysisExtraction, Rotation(BiasType, Extraction, Rotation) |
Constructs a C# DoubleFactorAnalysis C# Analyze | |
DoubleFactorAnalysisExtraction, Rotation(DoubleSymmetricMatrix, BiasType, Extraction) |
Constructs a C# DoubleFactorAnalysis C# Rotation | |
DoubleFactorAnalysisExtraction, Rotation(DoubleSymmetricMatrix, BiasType, Extraction, Rotation) |
Constructs a C# DoubleFactorAnalysis |
Name | Description | |
---|---|---|
CumulativeVarianceProportions | Gets the cumulative variance proportions. | |
ExtractedCommunalities | This is the proportion of each variable's variance that can be explained by the extracted factors jointly. The ith entry corresponds to the ith variable. | |
FactorExtraction | Gets the object that performs the factor extraction. | |
FactorRotation | Gets the object that performs the factor rotation. | |
Factors | Gets the extracted factors. Each column of the matrix is a factor. | |
InitialCommunalities | This is the proportion of each variable's variance that can be explained by the factors jointly. The ith entry corresponds to the ith variable. | |
MatrixData | Gets the matrix data from which factors were extracted. This is either the correlation matrix of the covariance matrix. | |
NumberOfFactors | The number of factors extracted. | |
RotatedFactors |
Gets the rotated factors (will be the same as C# Factors C# NoRotation | |
RotatedSumOfSquaredLoadings | Gets the sum of squared loadings for each rotated extracted factor. | |
SumOfSquaredLoadings | Gets the sum of squared loadings for each extracted factor. | |
VarianceProportions | Gets a vector of proportion of variance explained by each factor. The ith entry corresoponds to the ith factor. |
Name | Description | |
---|---|---|
AdjustFactorSigns | Adjusts the signs of the factors according to the convention that the sum of all factor components should be non-negative. Implemented to match SPSS output. | |
Analyze | Performs a factor analysis on the given symmetric covariance or correlation matrix for the data being analyzed. | |
Clone | Returns a deep copy of self. | |
ComputeCovarianceMatrix | Computes the covaraince matrix for the given data and bias type. The result is returned as a symmetric matrix object. | |
Rotate |
Performs factor rotation using the C# factorRotation_ | |
SortRotatedFactorsAndLoadings |
Sorts the rotated factor and rotated sum of squared loadings matrices in order
of descending variance of the rotated factors. Done mostly to match the output
of SPSS. The result is stored in the C# rotatedFactorMatrix_ | |
StandardizeData | Computes the standardized data - means 0 and variances 1. |
Name | Description | |
---|---|---|
bias_ | The bias type for all variance estimates. | |
factorExtraction_ | Factor extraction algorithm. | |
factorMatrix_ | The extracted factors. | |
factorRotation_ | Factor rotation algorithm. | |
matrixData_ | Matrix data being analyzed (correlation or covariance). | |
noRotation_ | Boolean variable indicating whether or not factor rotation was requested. | |
numberOfFactors_ | Number of factors to be extracted. | |
rotatedFactorMatrix_ | The rotated factors. |
NoRotation
FactorAnalysisCorrelation
FactorAnalysisCovariance