public class ConstrainedLASSObyLARS extends Object implements LinearModel
| Constructor and Description |
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ConstrainedLASSObyLARS(ConstrainedLASSOProblem problem)
Solves a constrained LASSO problem by modified least angle regression (LARS) and linear
interpolation.
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ConstrainedLASSObyLARS(ConstrainedLASSOProblem problem,
boolean demeaned,
boolean normalized,
double epsilon,
int maxIterations)
Solves a constrained LASSO problem by modified least angle regression (LARS) and linear
interpolation.
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| Modifier and Type | Method and Description |
|---|---|
LMBeta |
beta()
Gets \(\hat{\beta}\) and statistics.
|
double |
Ey(Vector x)
Computes the expectation \(E(y(x))\) given an input.
|
LMResiduals |
residuals()
Gets the residual analysis of an OLS regression.
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public ConstrainedLASSObyLARS(ConstrainedLASSOProblem problem, boolean demeaned, boolean normalized, double epsilon, int maxIterations)
problem - a constrained LASSO problemdemeaned - an indicator of whether an intercept is included in the modelnormalized - an indicator of whether the predictors are first normalized to have unit
L2 normepsilon - a precision parameter: when a number |x| ≤ ε, it is
considered 0maxIterations - the maximum number of iterationspublic ConstrainedLASSObyLARS(ConstrainedLASSOProblem problem)
problem - a constrained LASSO problempublic double Ey(Vector x)
LinearModelEy in interface LinearModelx - an inputpublic LMBeta beta()
LinearModelbeta in interface LinearModelpublic LMResiduals residuals()
LinearModelresiduals in interface LinearModelCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.