GeneralizedLinearModel Constructor

Definition

Namespace: Numerics.NET.Statistics
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4

Overload List

GeneralizedLinearModel(IDataFrame, String, String, String[])	Constructs a new binomial GeneralizedLinearModel.
GeneralizedLinearModel(Vector<Double>, Vector<Double>, Matrix<Double>, Vector<Double>)	Constructs a new binomial GeneralizedLinearModel.
GeneralizedLinearModel(Vector<Double>, Vector<Double>, Vector<Double>[], Vector<Double>)	Constructs a new binomial GeneralizedLinearModel.
GeneralizedLinearModel(IDataFrame, String, ModelFamily, LinkFunction, String)	Constructs a new GeneralizedLinearModel.
GeneralizedLinearModel(Vector<Double>, Matrix<Double>, ModelFamily, LinkFunction, Vector<Double>)	Constructs a new GeneralizedLinearModel.
GeneralizedLinearModel(Vector<Double>, IEnumerable<Vector<Double>>, ModelFamily, LinkFunction, Vector<Double>)	Constructs a new GeneralizedLinearModel.
GeneralizedLinearModel(IDataFrame, String, String[], ModelFamily, LinkFunction, String)	Constructs a new GeneralizedLinearModel.

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

Constructs a new binomial GeneralizedLinearModel.

public GeneralizedLinearModel(
	IDataFrame dataFrame,
	string dependentVariable,
	string countVariable,
	string[] independentVariables
)

Visual Basic

Public Sub New ( 
	dataFrame As IDataFrame,
	dependentVariable As String,
	countVariable As String,
	independentVariables As String()
)

C++/CLI

public:
GeneralizedLinearModel(
	IDataFrame^ dataFrame, 
	String^ dependentVariable, 
	String^ countVariable, 
	array<String^>^ independentVariables
)

new : 
        dataFrame : IDataFrame * 
        dependentVariable : string * 
        countVariable : string * 
        independentVariables : string[] -> GeneralizedLinearModel

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.

public GeneralizedLinearModel(
	Vector<double> dependentData,
	Vector<double> countData,
	Matrix<double> independentData,
	Vector<double>? weights = null
)

Visual Basic

Public Sub New ( 
	dependentData As Vector(Of Double),
	countData As Vector(Of Double),
	independentData As Matrix(Of Double),
	Optional weights As Vector(Of Double) = Nothing
)

C++/CLI

public:
GeneralizedLinearModel(
	Vector<double>^ dependentData, 
	Vector<double>^ countData, 
	Matrix<double>^ independentData, 
	Vector<double>^ weights = nullptr
)

new : 
        dependentData : Vector<float> * 
        countData : Vector<float> * 
        independentData : Matrix<float> * 
        ?weights : Vector<float> 
(* Defaults:
        let _weights = defaultArg weights null
*)
-> GeneralizedLinearModel

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

ArgumentNullException

dependentData is null.

-or-

independentData is null.

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

Constructs a new binomial GeneralizedLinearModel.

public GeneralizedLinearModel(
	Vector<double> dependentVariable,
	Vector<double> countVariable,
	Vector<double>[] independentVariables,
	Vector<double>? weights = null
)

Visual Basic

Public Sub New ( 
	dependentVariable As Vector(Of Double),
	countVariable As Vector(Of Double),
	independentVariables As Vector(Of Double)(),
	Optional weights As Vector(Of Double) = Nothing
)

C++/CLI

public:
GeneralizedLinearModel(
	Vector<double>^ dependentVariable, 
	Vector<double>^ countVariable, 
	array<Vector<double>^>^ independentVariables, 
	Vector<double>^ weights = nullptr
)

new : 
        dependentVariable : Vector<float> * 
        countVariable : Vector<float> * 
        independentVariables : Vector<float>[] * 
        ?weights : Vector<float> 
(* Defaults:
        let _weights = defaultArg weights null
*)
-> GeneralizedLinearModel

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

ArgumentNullException

dependentVariable is null.

-or-

independentVariables is null.

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

Constructs a new GeneralizedLinearModel.

public GeneralizedLinearModel(
	IDataFrame dataFrame,
	string formula,
	ModelFamily? family = null,
	LinkFunction? link = null,
	string? weightVariable = null
)

Visual Basic

Public Sub New ( 
	dataFrame As IDataFrame,
	formula As String,
	Optional family As ModelFamily = Nothing,
	Optional link As LinkFunction = Nothing,
	Optional weightVariable As String = Nothing
)

C++/CLI

public:
GeneralizedLinearModel(
	IDataFrame^ dataFrame, 
	String^ formula, 
	ModelFamily^ family = nullptr, 
	LinkFunction^ link = nullptr, 
	String^ weightVariable = nullptr
)

new : 
        dataFrame : IDataFrame * 
        formula : string * 
        ?family : ModelFamily * 
        ?link : LinkFunction * 
        ?weightVariable : string 
(* Defaults:
        let _family = defaultArg family null
        let _link = defaultArg link null
        let _weightVariable = defaultArg weightVariable null
*)
-> GeneralizedLinearModel

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

FormatException

The formula is not in the correct format.

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

Constructs a new GeneralizedLinearModel.

public GeneralizedLinearModel(
	Vector<double> dependentData,
	Matrix<double> independentData,
	ModelFamily? family = null,
	LinkFunction? link = null,
	Vector<double>? weights = null
)

Visual Basic

Public Sub New ( 
	dependentData As Vector(Of Double),
	independentData As Matrix(Of Double),
	Optional family As ModelFamily = Nothing,
	Optional link As LinkFunction = Nothing,
	Optional weights As Vector(Of Double) = Nothing
)

C++/CLI

public:
GeneralizedLinearModel(
	Vector<double>^ dependentData, 
	Matrix<double>^ independentData, 
	ModelFamily^ family = nullptr, 
	LinkFunction^ link = nullptr, 
	Vector<double>^ weights = nullptr
)

new : 
        dependentData : Vector<float> * 
        independentData : Matrix<float> * 
        ?family : ModelFamily * 
        ?link : LinkFunction * 
        ?weights : Vector<float> 
(* Defaults:
        let _family = defaultArg family null
        let _link = defaultArg link null
        let _weights = defaultArg weights null
*)
-> GeneralizedLinearModel

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

ArgumentNullException

dependentData is null.

-or-

independentData is null.

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

Constructs a new GeneralizedLinearModel.

public GeneralizedLinearModel(
	Vector<double> dependentVariable,
	IEnumerable<Vector<double>> independentVariables,
	ModelFamily? family = null,
	LinkFunction? link = null,
	Vector<double>? weights = null
)

Visual Basic

Public Sub New ( 
	dependentVariable As Vector(Of Double),
	independentVariables As IEnumerable(Of Vector(Of Double)),
	Optional family As ModelFamily = Nothing,
	Optional link As LinkFunction = Nothing,
	Optional weights As Vector(Of Double) = Nothing
)

C++/CLI

public:
GeneralizedLinearModel(
	Vector<double>^ dependentVariable, 
	IEnumerable<Vector<double>^>^ independentVariables, 
	ModelFamily^ family = nullptr, 
	LinkFunction^ link = nullptr, 
	Vector<double>^ weights = nullptr
)

new : 
        dependentVariable : Vector<float> * 
        independentVariables : IEnumerable<Vector<float>> * 
        ?family : ModelFamily * 
        ?link : LinkFunction * 
        ?weights : Vector<float> 
(* Defaults:
        let _family = defaultArg family null
        let _link = defaultArg link null
        let _weights = defaultArg weights null
*)
-> GeneralizedLinearModel

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

ArgumentNullException

dependentVariable is null.

-or-

independentVariables is null.

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

Constructs a new GeneralizedLinearModel.

public GeneralizedLinearModel(
	IDataFrame dataFrame,
	string dependentVariable,
	string[] independentVariables,
	ModelFamily? family = null,
	LinkFunction? link = null,
	string? weightVariable = null
)

Visual Basic

Public Sub New ( 
	dataFrame As IDataFrame,
	dependentVariable As String,
	independentVariables As String(),
	Optional family As ModelFamily = Nothing,
	Optional link As LinkFunction = Nothing,
	Optional weightVariable As String = Nothing
)

C++/CLI

public:
GeneralizedLinearModel(
	IDataFrame^ dataFrame, 
	String^ dependentVariable, 
	array<String^>^ independentVariables, 
	ModelFamily^ family = nullptr, 
	LinkFunction^ link = nullptr, 
	String^ weightVariable = nullptr
)

new : 
        dataFrame : IDataFrame * 
        dependentVariable : string * 
        independentVariables : string[] * 
        ?family : ModelFamily * 
        ?link : LinkFunction * 
        ?weightVariable : string 
(* Defaults:
        let _family = defaultArg family null
        let _link = defaultArg link null
        let _weightVariable = defaultArg weightVariable null
*)
-> GeneralizedLinearModel

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.

GeneralizedLinearModel Constructor

Definition

Overload List

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

Parameters

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

Parameters

Exceptions

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

Parameters

Exceptions

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

Parameters

Exceptions

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

Parameters

Exceptions

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

Parameters

Exceptions

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

Parameters

See Also

Reference