Added new function relax.islasso(), which allows
fitting a relaxed islasso model by selecting variables to remain
unpenalized. Variables can be specified either by name or by index, or
automatically selected according to a significance level
(alpha). This extension provides additional flexibility in
post-selection inference.
Some bugs fixed.
islasso 1.6.0 (2025-07-30)
Performance & Refactoring
Core computational routines have been cleaned up, and some bugs have
been fixed.
Legacy R routines have been revised, cleaned, and commented. Minor
inconsistencies have been addressed.
Documentation
Help files and function manuals are now fully managed via
roxygen2, with substantial updates to usage examples and
descriptions.
Visualization
All plotting functions have been refactored to use the
ggplot2 framework for consistent and modern graphics.
User Experience
A custom ASCII startup banner has been added on package attach,
providing a welcoming and informative message.
islasso 1.5.1
Some bugs fixed.
islasso 1.5.0
Some bugs fixed.
Other S3 methods implemented.
islasso 1.4.3
Some bugs fixed.
islasso 1.4.2
Some bugs for binomial family fixed.
islasso 1.4.1
Some bugs fixed.
islasso 1.4.0
New optimization algorithm for the ‘islasso’ method. The algorithm
is now stable for all the implemented distributions.
In aic.islasso() function the available methods are
“AIC”, “BIC”, “AICc”, “eBIC”, “GCV”, “GIC”.
New class of functions named islasso.path created. The
main function islasso.path() builds the coefficient profile
for a fixed sequence of lambda values.
New function GoF.islasso.path() extracts the optimal
tuning parameter minimizing a fixed criterion. Available criteria are
the same as in aic.islasso().
Some bugs fixed.
islasso 1.3.1
Some bugs fixed.
islasso 1.3.0
Vignette added to the package.
Some bugs fixed.
islasso 1.2.3
Some bugs fixed.
islasso 1.2.2
Some bugs fixed.
islasso 1.2.1
Some bugs fixed.
islasso 1.2.0
New implementation of the estimating algorithm. Now islasso is much
stabler and faster.
New function: general linear hypotheses for linear combinations of
the regression coefficients, including confidence intervals.
Prediction function includes confidence intervals for the fitted
values.
Step halving with Armijo’s rule improved.
Convergence criterion improved.
Some bugs fixed.
islasso 1.1.0
New implementation of the estimating algorithm. Now islasso is much
stabler and faster, reducing the number of iterations to reach
convergence.
Step halving with Armijo’s rule implemented.
Elastic-net approach added via alpha parameter in the
objective function (as in glmnet).
Summary method now includes degrees of freedom for each covariate,
with choice between t-test or z-test (only for Gaussian family).
optim.islasso renamed to aic.islasso;
interval specification no longer required.
islasso.control renamed to is.control;
control parameters modified.
Two trace versions implemented in is.control: compact
(trace = 1) and verbose (trace = 2).