islasso 1.6.2 (2025-11-15)
islasso 1.6.1 (2025-11-13)
- Created GitHub page and website.
- Created introductory vignette.
- Fortran routines updated and speeded up (~2x).
- Manuals updated.
- 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)
- 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
islasso 1.5.0
- Some bugs fixed.
- Other S3 methods implemented.
islasso 1.4.3
islasso 1.4.2
- Some bugs for binomial family fixed.
islasso 1.4.1
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
islasso 1.3.0
- Vignette added to the package.
- Some bugs fixed.
islasso 1.2.3
islasso 1.2.2
islasso 1.2.1
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).
- Some bugs fixed.