public class OLSRegression extends Object implements LinearModel
Constructor and Description |
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OLSRegression(LMProblem problem)
Constructs an OLSRegression instance.
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OLSRegression(LMProblem problem,
double epsilon)
Constructs an OLSRegression instance.
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Modifier and Type | Method and Description |
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OLSBeta |
beta()
Gets \(\hat{\beta}\) and statistics.
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LMDiagnostics |
diagnostics()
Gets the diagnostic measures of an OLS regression.
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double |
Ey(Vector x)
Computes the expectation \(E(y(x))\) given an input.
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static double |
Ey(Vector beta,
Vector x,
boolean intercept) |
LMInformationCriteria |
informationCriteria()
Gets the model selection criteria.
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OLSResiduals |
residuals()
Gets the residual analysis of an OLS regression.
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public OLSRegression(LMProblem problem, double epsilon)
problem
- the linear regression problem to be solvedepsilon
- a precision parameter: when a number |x| ≤ ε, it is considered 0public OLSRegression(LMProblem problem)
problem
- the linear regression problem to be solvedpublic double Ey(Vector x)
LinearModel
Ey
in interface LinearModel
x
- an inputpublic OLSBeta beta()
LinearModel
beta
in interface LinearModel
public OLSResiduals residuals()
LinearModel
residuals
in interface LinearModel
public LMDiagnostics diagnostics()
public LMInformationCriteria informationCriteria()
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