Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET

  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Blog
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Nuget packages
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • Extreme Optimization
    • Features
    • Solutions
    • Documentation
    • QuickStart Samples
    • Sample Applications
    • Downloads
    • Technical Support
    • Download trial
    • How to buy
    • Blog
    • Company
    • Resources
  • Documentation
    • Introduction
    • Deployment Guide
    • Nuget packages
    • Configuration
    • Using Parallelism
    • Mathematics Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Data Access Library User's Guide
    • Reference
  • Reference
    • Extreme
    • Extreme.Collections
    • Extreme.Data
    • Extreme.Data.Json
    • Extreme.Data.Matlab
    • Extreme.Data.R
    • Extreme.Data.Stata
    • Extreme.Data.Text
    • Extreme.DataAnalysis
    • Extreme.DataAnalysis.Linq
    • Extreme.DataAnalysis.Models
    • Extreme.Mathematics
    • Extreme.Mathematics.Algorithms
    • Extreme.Mathematics.Calculus
    • Extreme.Mathematics.Calculus.OrdinaryDifferentialEquations
    • Extreme.Mathematics.Curves
    • Extreme.Mathematics.Curves.Nonlinear
    • Extreme.Mathematics.Distributed
    • Extreme.Mathematics.EquationSolvers
    • Extreme.Mathematics.Generic
    • Extreme.Mathematics.LinearAlgebra
    • Extreme.Mathematics.LinearAlgebra.Implementation
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers.Preconditioners
    • Extreme.Mathematics.Optimization
    • Extreme.Mathematics.Optimization.LineSearches
    • Extreme.Mathematics.Random
    • Extreme.Mathematics.SignalProcessing
    • Extreme.Providers
    • Extreme.Providers.InteropServices
    • Extreme.Statistics
    • Extreme.Statistics.Distributions
    • Extreme.Statistics.Multivariate
    • Extreme.Statistics.Tests
    • Extreme.Statistics.TimeSeriesAnalysis
  • Extreme.DataAnalysis.Models
    • ClassificationModel(T) Class
    • ClusteringModel(T) Class
    • ITransformationModel Interface
    • Model Class
    • ModelExtensions Class
    • ModelFitOptions Class
    • ModelInput Class
    • ModelInputCategory Enumeration
    • ModelInputFormat Enumeration
    • ModelInputGroup Class
    • ModelSerialization Enumeration
    • ModelStatus Enumeration
    • ModelTerm Class
    • ModelTermCollection Class
    • ModelTermKind Enumeration
    • RegressionModel(T) Class
    • TransformationModel(T) Class
  • RegressionModel(T) Class
    • RegressionModel(T) Constructor
    • Properties
    • Methods
  • Properties
    • AdjustedRSquared Property
    • AnovaTable Property
    • CovarianceMatrix Property
    • DegreesOfFreedom Property
    • DependentVariable Property
    • FStatistic Property
    • IndependentVariables Property
    • LogLikelihood Property
    • Parameters Property
    • ParameterValues Property
    • Predictions Property
    • PValue Property
    • Residuals Property
    • ResidualSumOfSquares Property
    • RSquared Property
    • StandardError Property

RegressionModelT Properties

Extreme Optimization Numerical Libraries for .NET Professional

The RegressionModelT generic type exposes the following members.

Properties

  NameDescription
Public propertyAdjustedRSquared
Gets the adjusted R Squared value for the regression.
Public propertyAnovaTable
Gets the AnovaTable that summarizes the results of this model.
Public propertyBaseFeatureIndex
Gets an index containing the keys of the columns that are required inputs to the model.
(Inherited from Model.)
Public propertyComputed Obsolete.
Gets whether the model has been computed.
(Inherited from Model.)
Public propertyCovarianceMatrix
Gets the covariance matrix of the model parameters.
Public propertyData
Gets an object that contains all the data used as input to the model.
(Inherited from Model.)
Public propertyDegreesOfFreedom
Gets the total degrees of freedom of the data.
Public propertyDependentVariable
Gets a vector that contains the dependent variable that is to be fitted.
Public propertyFitted
Gets whether the model has been computed.
(Inherited from Model.)
Public propertyFStatistic
Gets the F statistic for the regression.
Public propertyIndependentVariables
Gets a matrix whose columns contain the independent variables in the model.
Public propertyInputSchema
Gets the schema for the features used for fitting the model.
(Inherited from Model.)
Public propertyLogLikelihood
Gets the log-likelihood that the model generated the data.
Public propertyMaxDegreeOfParallelism
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model.)
Public propertyModelSchema
Gets the collection of variables used in the model.
(Inherited from Model.)
Public propertyNumberOfObservations
Gets the number of observations the model is based on.
(Inherited from Model.)
Protected propertyParallelOptions
Gets or sets an object that specifies how the calculation of the model should be parallelized.
(Inherited from Model.)
Public propertyParameters
Gets the collection of parameters associated with this model.
Public propertyParameterValues
Gets the values of the parameters associated with this model.
Public propertyPredictions
Gets a vector containing the model's predicted values for the dependent variable.
Public propertyPValue
Gets the probability corresponding to the F statistic for the regression.
Public propertyResiduals
Gets a vector containing the residuals of the model.
Public propertyResidualSumOfSquares
Gets the sum of squares of the residuals of the model.
Public propertyRSquared
Gets the R Squared value for the regression.
Public propertyStandardError
Gets the standard error of the regression.
Public propertyStatus
Gets the status of the model, which determines which information is available.
(Inherited from Model.)
Public propertySupportsWeights
Indicates whether the model supports case weights.
(Inherited from Model.)
Public propertyWeights
Gets or sets the actual weights.
(Inherited from Model.)
Top
See Also

Reference

RegressionModelT Class
Extreme.DataAnalysis.Models Namespace

Copyright (c) 2004-2021 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-2021, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.