GeneralizedLinearModel Constructor

Definition

Namespace: Extreme.Statistics
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

Overload List

GeneralizedLinearModel(IDataFrame, String, String, String[])

Constructs a new binomial GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	IDataFrame dataFrame,
	string dependentVariable,
	string countVariable,
	string[] independentVariables
)

Parameters

dataFrame  IDataFrame
A data frame containing the data for the regression.
dependentVariable  String
The name of the variable that contains the number of successes.
countVariable  String
The name of the variable that contains the total number of trials.
independentVariables  String[]
An array containing the names of the independent variable.

GeneralizedLinearModel(Vector<Double>, Vector<Double>, Matrix<Double>, Vector<Double>)

Constructs a new binomial GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	Vector<double> dependentData,
	Vector<double> countData,
	Matrix<double> independentData,
	Vector<double> weights = null
)

Parameters

dependentData  Vector<Double>
A vector that contains the number of successful trials.
countData  Vector<Double>
A vector that contains the total number of trials.
independentData  Matrix<Double>
A matrix that contains the data for the independent variables.
weights  Vector<Double>  (Optional)
(Optional.) A vector that contains the weight for each observation.

Exceptions

ArgumentNullExceptiondependentData is null.
-or-
independentData is null.

GeneralizedLinearModel(Vector<Double>, Vector<Double>, Vector<Double>[], Vector<Double>)

Constructs a new binomial GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	Vector<double> dependentVariable,
	Vector<double> countVariable,
	Vector<double>[] independentVariables,
	Vector<double> weights = null
)

Parameters

dependentVariable  Vector<Double>
A vector that contains the number of successful trials for each observation.
countVariable  Vector<Double>
A vector that contains the total number of trials for each observation.
independentVariables  Vector<Double>[]
An array of vectors that contain the independent variables.
weights  Vector<Double>  (Optional)
(Optional.) A vector that contains the weight for each observation.

Exceptions

ArgumentNullExceptiondependentVariable is null.

-or-

independentVariables is null.

GeneralizedLinearModel(IDataFrame, String, ModelFamily, LinkFunction, String)

Constructs a new GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	IDataFrame dataFrame,
	string formula,
	ModelFamily family = null,
	LinkFunction link = null,
	string weightVariable = null
)

Parameters

dataFrame  IDataFrame
A data frame containing the data for the regression.
formula  String
A formula that specifies the variables in the model. It should not include the link function.
family  ModelFamily  (Optional)
Optional. The probability distribution family of the model.
link  LinkFunction  (Optional)
Optional. The link function of the model. The default is the canonical link function for family.
weightVariable  String  (Optional)
The name of the variable that contains the case weights. May be null.

Exceptions

FormatExceptionThe formula is not in the correct format.

GeneralizedLinearModel(Vector<Double>, Matrix<Double>, ModelFamily, LinkFunction, Vector<Double>)

Constructs a new GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	Vector<double> dependentData,
	Matrix<double> independentData,
	ModelFamily family = null,
	LinkFunction link = null,
	Vector<double> weights = null
)

Parameters

dependentData  Vector<Double>
A vector that contains the data for the dependent variable.
independentData  Matrix<Double>
A matrix that contains the data for the independent variable.
family  ModelFamily  (Optional)
Optional. The probability distribution family of the model.
link  LinkFunction  (Optional)
Optional. The link function of the model.
weights  Vector<Double>  (Optional)
(Optional.) A vector that contains the weight for each observation.

Exceptions

ArgumentNullExceptiondependentData is null.
-or-
independentData is null.

GeneralizedLinearModel(Vector<Double>, IEnumerable<Vector<Double>>, ModelFamily, LinkFunction, Vector<Double>)

Constructs a new GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	Vector<double> dependentVariable,
	IEnumerable<Vector<double>> independentVariables,
	ModelFamily family = null,
	LinkFunction link = null,
	Vector<double> weights = null
)

Parameters

dependentVariable  Vector<Double>
A vector that specifies the dependent variable.
independentVariables  IEnumerable<Vector<Double>>
An array of vectors that contain the independent variables.
family  ModelFamily  (Optional)
Optional. The probability distribution family of the model.
link  LinkFunction  (Optional)
Optional. The link function of the model.
weights  Vector<Double>  (Optional)
(Optional.) A vector containing the weight associated with each observation.

Exceptions

ArgumentNullExceptiondependentVariable is null.

-or-

independentVariables is null.

GeneralizedLinearModel(IDataFrame, String, String[], ModelFamily, LinkFunction, String)

Constructs a new GeneralizedLinearModel.
C#
public GeneralizedLinearModel(
	IDataFrame dataFrame,
	string dependentVariable,
	string[] independentVariables,
	ModelFamily family = null,
	LinkFunction link = null,
	string weightVariable = null
)

Parameters

dataFrame  IDataFrame
A data frame containing the data for the regression.
dependentVariable  String
The name of the dependent variable.
independentVariables  String[]
An array containing the names of the independent variable.
family  ModelFamily  (Optional)
Optional. The probability distribution family of the model.
link  LinkFunction  (Optional)
Optional. The link function of the model.
weightVariable  String  (Optional)
The name of the variable that contains the case weights. May be null.

See Also