NEWS.md
tol_rel_coef_change
argument to SLOPE()
as a convergence criterion for the FISTA solver that sets a tolerance for the relative change in coefficients across iterations.std::sqrt()
in src/SLOPE.cpp
.alpha
(previously sigma
) is now invariant to the number of observations, which is achieved by scaling the penalty part of the objective by the square root of the number of observations if scale = "l2"
and the number of observations if scale = "sd"
or "none"
. No scaling is applied when scale = "l1"
.sigma
argument is deprecated in favor of alpha
in SLOPE()
, coef.SLOPE()
, and predict.SLOPE()
.n_sigma
argument is deprecated in favor of path_length
in SLOPE()
lambda_min_ratio
argument is deprecated in favor of alpha_min_ratio
in SLOPE()
lambda
in SLOPE()
has changed from "gaussian"
to "bh"
.scale = "sd"
now scales with the population standard deviation rather than the sample standard deviation, i.e. the scaling factor now used is the number of observations (and not the number of observations minus one as before).path_length
has changed from 100 to 20.plot.SLOPE()
has gained an argument x_variable
that controls what is plotted on the x axis.max_variables
criterion is hit, the solution path returned will now include also the last solution (which was not the case before). Thanks, @straw-boy.deviance()
and SLOPE()
that were taking too long to execute have been removed or modified.This version of SLOPE represents a major change to the package. We have merged functionality from the owl package into this package, which means there are several changes to the API, including deprecated functions.
SLOPE_solver()
, SLOPE_solver_matlab()
, prox_sorted_L1()
, and create_lambda()
have been deprecated (and will be defunct in the next version of SLOPE)X
, fdr
, and normalize
have been deprecated in SLOPE()
and replaced by x
, q
, scale
and center
, respectively"default"
and "matlab"
to argument solver
in SLOPE()
have been deprecated and replaced with "fista"
and "admm"
, which uses the accelerated proximal gradient method FISTA and alternating direction of multipliers method (ADMM) respectivelyfamily = "gaussian"
family
argument in SLOPE()
)lambda
is now scaled (divided by) the number of observations (rows) in x
screen = TRUE
in SLOPE()
. The type of algorithm can also be set via screen_alg
.SLOPE()
now returns an object of class "SLOPE"
(and an additional class depending on input to family
in SLOPE()
SLOPE
objects gain coef()
and plot()
methods.SLOPE
now uses screening rules to speed up model fitting in the high-dimensional regimetrainSLOPE()
trains SLOPE with repeated k-folds cross-validationcaretSLOPE()
enables model-tuning using the caret packageSLOPE()
now fits an entire path of regularization sequences by defaultnormalize
option to SLOPE()
has been replaced by scale
and center
, which allows granular options for standardizationdeviance()
returns the deviance from the fitscore()
can be used to assess model performance against new dataplotDiagnostics()
has been included to visualize data from the solver (if diagnostics = TRUE
in the call to SLOPE()
)lambda = "oscar" in the call to
SLOPE()`