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Main functions for user

Functions for fitting various structured regularization models

bounded.reg()
Fit a linear model with infinity-norm plus ridge-like regularization
elastic.net()
Fit a linear model with elastic-net regularization
fusedlasso()
A function for fitting generalized fused-Lasso problems
lava()
Fit a linear model with lava regularization
lasso()
Fit a linear model with lasso regularization
ridge()
Fit a linear model with a structured ridge regularization

Classes and methods for handling the Quadrupen fits

R6 Classes for the user to manipulate the ouput of the main functions

QuadrupenFit
Class "QuadrupenFit"
ElasticNetFit
Class "ElasticNetFit"
FusedLassoFit
Class "FusedLassoFit"
LavaFit
Class "LavaFit"
BoundedRegressionFit
Class "BoundedRegression"
RidgeRegressionFit
Class "RidgeRegressionFit"

Auxiliaries Classes and methods

R6 Classes used as fields of the main Class Quadrupen fit

DataModel
Data Class
CrossValidation
Class CrossValidation
StabilityPath
Class StabilityPath
InformationCriteria
Class InformationCriteria

Auxiliaries S3 methods

S3 methods, aliases for the most useful R6 methods.

criteria()
Penalized criteria based on estimation of degrees of freedom
cross_validate()
Cross-validation for Quadrupen object
stability()
Stability selection for Quadrupen object
residuals(<QuadrupenFit>)
Extract model residuals
coef(<QuadrupenFit>)
Extract model coefficients
predict(<QuadrupenFit>)
Perform model prediction
fitted(<QuadrupenFit>)
Extracts model fitted values
deviance(<QuadrupenFit>)
Extract model deviance
isQuadrupenFit()
Auxiliary functions to check the given class of an object