Class ConstrainedLASSObyLARS
- java.lang.Object
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- dev.nm.stat.regression.linear.lasso.ConstrainedLASSObyLARS
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- All Implemented Interfaces:
LinearModel
public class ConstrainedLASSObyLARS extends Object implements LinearModel
This class solves the constrained form of LASSO by modified least angle regression (LARS) and linear interpolation: \[ \min_w \left \{ \left \| Xw - y \right \|_2^2 \right \}\) subject to \( \left \| w \right \|_1 \leq t \]- See Also:
- B. Efron et. al, "Least Angle Regression," The Annals of Statistics, Volume: 32(2), 407 - 499, 2004.
- T. Hastie, R. Tibshirani and J. Friedman, "The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Second Edition)," New York, Springer-Verlag, 2009.
- Wikipedia: LASSO method
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Constructor Summary
Constructors Constructor Description ConstrainedLASSObyLARS(ConstrainedLASSOProblem problem)
Solves a constrained LASSO problem by modified least angle regression (LARS) and linear interpolation.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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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method 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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Constructor Detail
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ConstrainedLASSObyLARS
public 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.- Parameters:
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 iterations
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ConstrainedLASSObyLARS
public ConstrainedLASSObyLARS(ConstrainedLASSOProblem problem)
Solves a constrained LASSO problem by modified least angle regression (LARS) and linear interpolation.- Parameters:
problem
- a constrained LASSO problem
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Method Detail
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Ey
public double Ey(Vector x)
Description copied from interface:LinearModel
Computes the expectation \(E(y(x))\) given an input.- Specified by:
Ey
in interfaceLinearModel
- Parameters:
x
- an input- Returns:
- \(E(y(x))\)
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beta
public LMBeta beta()
Description copied from interface:LinearModel
Gets \(\hat{\beta}\) and statistics.- Specified by:
beta
in interfaceLinearModel
- Returns:
- \(\hat{\beta}\) and statistics
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residuals
public LMResiduals residuals()
Description copied from interface:LinearModel
Gets the residual analysis of an OLS regression.- Specified by:
residuals
in interfaceLinearModel
- Returns:
- the residual analysis
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