 | LinearRegression Class |
Class LinearRegression computes a multiple linear regression from an input
matrix of independent variable values and vector of dependent variable
values.
Inheritance HierarchyNamespace: CenterSpace.NMath.Core
Assembly: NMath (in NMath.dll) Version: 7.3
SyntaxThe LinearRegression type exposes the following members.
Constructors| 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.
|
Properties| 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.
|
Methods| 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.
|
Fields| 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 paramters.
(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.) |
See Also