![]() | Linear |
The LinearRegression type exposes the following members.
Name | Description | |
---|---|---|
![]() | LinearRegression | Default constructor. Constructs a LinearRegression instance with all sizes equal to zero. |
![]() | LinearRegression(DataFrame, IDFColumn) | Constructs a LinearRegression instance with the specifed regresssion data and observation column. By default, the model parameter values are computed using a QR factorization. |
![]() | LinearRegression(DataFrame, Int32) | Constructs a LinearRegression instance with the specifed regresssion data and an index to the observation column. By default, the model parameter values are computed using a QR factorization. |
![]() | LinearRegression(DoubleMatrix, DoubleVector) | Constructs a LinearRegression instance with the specifed regresssion matrix and observation vector. By default, the model parameter values are computed using a QR factorization. |
![]() | LinearRegression(DataFrame, IDFColumn, IRegressionCalculation) | Constructs a LinearRegression instance with the specifed regresssion data and observation column. Model parameter values are computed using the specified regression calculator. |
![]() | LinearRegression(DataFrame, IDFColumn, Boolean) | Constructs a LinearRegression instance with the specifed regresssion data and observation column, optionally adding an intercept parameter. By default, the model parameter values are computed using a QR factorization. |
![]() | LinearRegression(DataFrame, Int32, IRegressionCalculation) | Constructs a LinearRegression instance with the specifed regresssion data and an index to the observation column. Model parameter values are computed using the specified regression calculator. |
![]() | LinearRegression(DataFrame, Int32, Boolean) | Constructs a LinearRegression instance with the specifed regresssion data and an index to the observation column, optionally adding an intercept parameter. By default, the model parameter values are computed using a QR factorization. |
![]() | LinearRegression(DoubleMatrix, DoubleVector, IRegressionCalculation) | Constructs a LinearRegression instance with the specifed regresssion matrix and observation vector. Model parameter values are computed using the specified regression calculator. |
![]() | LinearRegression(DoubleMatrix, DoubleVector, Boolean) | Constructs a LinearRegression instance with the specifed regresssion matrix and observation vector, optionally adding an intercept parameter. By default, the model parameter values are computed using a QR factorization. |
![]() | LinearRegression(DataFrame, IDFColumn, Boolean, IRegressionCalculation) | Constructs a LinearRegression instance with the specifed regresssion data and observation column, optionally adding an intercept parameter. The model parameter values are computed using the specified regression calculator. |
![]() | LinearRegression(DataFrame, Int32, Boolean, IRegressionCalculation) | Constructs a LinearRegression instance with the specifed regresssion data and an index to the observation column, optionally adding an intercept parameter. The model parameter values are computed using the specified regression calculator. |
![]() | LinearRegression(DoubleMatrix, DoubleVector, Boolean, IRegressionCalculation) | Constructs a LinearRegression instance with the specifed regresssion matrix and observation vector, optionally adding an intercept parameter. The model parameter values are computed using the specified regression calculator. |
Name | Description | |
---|---|---|
![]() | CheckData | Gets and sets a boolean indicating whether or not to check input data for non-numeric values. If input data is large checking all values for NaN's and infinities can be a performance consideration. |
![]() | ColumnResizeIncrement |
Gets and sets the amount by which the regression matrix is resized
if columns are added.
(Inherited from RegressionBase) |
![]() | CovarianceMatrix | Gets the covariance matrix. |
![]() | HasInterceptParameter |
Returns true if the model has an intercept parameter; otherwise,
false.
(Inherited from RegressionBase) |
![]() | Intercept |
Gets the intercept.
(Inherited from RegressionBase) |
![]() | IsGood |
Returns true if the model parameters were successfuly computed;
otherwise, false.
(Inherited from RegressionBase) |
![]() | NumberOfObservations |
Gets the number of observations.
(Inherited from RegressionBase) |
![]() | NumberOfParameters |
Gets the number of parameters in the model.
(Inherited from RegressionBase) |
![]() | NumberOfPredictors |
Gets the number of predictors.
(Inherited from RegressionBase) |
![]() | Observations |
Gets the vector of observations.
(Inherited from RegressionBase) |
![]() | ParameterCalculationErrorMessage |
Gets the error message associated with a failed parameter calculation.
(Inherited from RegressionBase) |
![]() | ParameterEstimates | Gets an array of parameter objects which may be used to perform hypothesis tests on individual parameters in the model. |
![]() | Parameters |
Gets the computed model parameters.
(Inherited from RegressionBase) |
![]() | PredictorMatrix |
Gets the predictor matrix.
(Inherited from RegressionBase) |
![]() | RegressionCalculator | Gets and sets the regression calculation object used for computing the model parameters. |
![]() | RegressionMatrix |
Gets the regression matrix.
(Inherited from RegressionBase) |
![]() | Residuals | Get the vector of residuals. |
![]() | RowResizeIncrement |
Gets and sets the amount by which the regression matrix is resized
if rows are added.
(Inherited from RegressionBase) |
![]() | Variance | Gets an estimate of the variance. |
Name | Description | |
---|---|---|
![]() | AddInterceptParameter |
Adds an intercept parameter to the model and recalculates the model parameters.
(Inherited from RegressionBase) |
![]() | AddObservation |
Adds the given observation to the model, and recalculates the model parameters.
(Inherited from RegressionBase) |
![]() | AddObservations |
Adds the given observations to the model, and recalculates the model parameters.
(Inherited from RegressionBase) |
![]() | AddPredictor |
Adds a predictor to the model, and recalculates the model parameters.
(Inherited from RegressionBase) |
![]() | AddPredictors |
Adds predictors to the model, and recalculates the model parameters.
(Inherited from RegressionBase) |
![]() | Clone | Creates a deep copy of this LinearRegression. |
![]() | GetStandardizedResiduals | Returns the standardized residuals (also known as the internally studentized residuals). |
![]() | GetStudentizedResiduals | Returns the (externally) studentized residuals. |
![]() | PredictedObservation | Returns the value of the dependent variable predicted by the model for the given set of predictor values. |
![]() | PredictedObservations | Returns the values of the dependent variable predicted by the model for the given sets of predictor values. |
![]() | PredictionInterval | Returns a confidence interval for the value of the dependent variable predicted by the model for the given set of predictor values. |
![]() | RecalculateParameters |
Recalculates the model parameters.
(Overrides RegressionBaseRecalculateParameters) |
![]() | RemoveInterceptParameter |
Removes the intercept parameter from the model, and recalculates the model parameters.
(Inherited from RegressionBase) |
![]() | RemoveObservation |
Removes the row at the indicated index from the predictor matrix and the
corresponding element from the observation vector, and recalculates the model
parameters.
(Inherited from RegressionBase) |
![]() | RemoveObservations |
Removes the specified rows from the predictor matrix, and recalculates the model
parameters.
(Inherited from RegressionBase) |
![]() | RemovePredictor |
Removes the specified predictor from the model, and recalculates the
model parameters.
(Inherited from RegressionBase) |
![]() ![]() | RemovePredictors |
Removes the specified predictors from the model, and recalculates the model
parameters.
(Inherited from RegressionBase) |
![]() | SetRegressionData(DataFrame, IDFColumn, Boolean) | Sets the regression matrix, observation vector, and intercept option to the specified values, and recalculates the model parameters. |
![]() | SetRegressionData(DoubleMatrix, DoubleVector, Boolean) | Sets the regression matrix, observation vector, and intercept option to the specified values, and recalculates the model parameters. |
![]() | VarianceInflationFactor | An index which measures how much the variance of a coefficient (square of the standard deviation) is increased because of collinearity. |
![]() | VarianceInflationFactors | An index which measures how much the variance of a coefficient (square of the standard deviation) is increased because of collinearity. |
Name | Description | |
---|---|---|
![]() | colResizeIncrement_ |
Number of columns to add when adding variables (if needed).
(Inherited from RegressionBase) |
![]() ![]() | DEFAULT_REGRESSION_CALCULATION | Default regression calculation is QRRegressionCalculation. |
![]() | errorMessage_ |
Explains errors, if any.
(Inherited from RegressionBase) |
![]() | hasIntercept_ |
Does the model have an intercept parameter?
(Inherited from RegressionBase) |
![]() | isGood_ |
Is the regression good?
(Inherited from RegressionBase) |
![]() | observationData_ |
Full set of observations.
(Inherited from RegressionBase) |
![]() | observations_ |
Subvector of the observation data used in the current regression model.
observations_ = observationData_[regMatRowSlice_].
(Inherited from RegressionBase) |
![]() | parameters_ |
Model parameters.
(Inherited from RegressionBase) |
![]() | regMatColSlice_ |
regressionMatrx_ = regressionData_[regMatRowSlice_, regMatColSlice_]
(Inherited from RegressionBase) |
![]() | regMatRowSlice_ |
regressionMatrx_ = regressionData_[regMatRowSlice_, regMatColSlice_]
(Inherited from RegressionBase) |
![]() | regressionData_ |
The full set of regression data.
(Inherited from RegressionBase) |
![]() | regressionMatrix_ |
A submatrix of the regression used in this regression
model.
regressionMatrx_ = regressionData_[regMatRowSlice_, regMatColSlice_]
(Inherited from RegressionBase) |
![]() | rowResizeIncrement_ |
Number of rows to add when adding observations (if needed).
(Inherited from RegressionBase) |