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Changelog

glmnet 5.0 Series

CRAN release: 2026-05-04

5.2 (development)

  • cv.glmnet() now takes nzero from the fitted object’s df instead of recomputing it. For multinomial and mgaussian fits, nzero is now the number of variables with a nonzero coefficient in any class or response. Previously ungrouped multinomial fits reported the median of the per-class counts, and grouped multinomial and mgaussian fits counted the intercept as a variable. nzero (and nzero.min/nzero.1se for relaxed fits) no longer carries names.
  • predict() and coef() on relaxed fits now accept a vector of gamma values, returning a list of results named by gamma. This path previously always failed (could not find function "outlist").
  • The coxdev submodule moves to 0.3.0, which fixes the diagonal of the Hessian with Efron’s ties at tied failure times. It is used as the IRLS weights, so Efron fits with tied failures may take different iterations, though they converge to the same solution. It is also what coxgrad(..., diag.hessian = TRUE) returns.
  • Unpenalized Cox fits (lambda = 0) now converge when a coefficient is held at lower.limits or upper.limits; previously the convergence check never passed in that case.
  • The coxgrad() documentation now says that the "diag_hessian" attribute is the diagonal of the Hessian of the deviance, i.e. -2 times the derivative of the returned gradient, not the Hessian of the log partial likelihood.

5.1 (2026-09-23)

Allow for the penalty.factor argument to be a function, as it is for exclude. Allows for seemless CV, when this function can depend on the response.

5.0 (2026-04-27)

First release since v4.1-10 (July 2025). Major rearchitecture with Cox speedups, a new per-call algorithm-control mechanism, and two new vignettes.

Architecture

  • All Fortran removed; glmnetpp and coxdev are now git submodules.
  • Cox is a first-class GLM type in glmnetpp; Cox deviance handled by coxdev (stratified and unstratified).
  • Cox speedups vs CRAN 4.1-10 on current hardware: ~2× dense, 5–11× sparse, 10–70× stratified. Non-Cox families unchanged and bit-identical.

Cox interface

  • New cox.ties = c("breslow", "efron"); default is "breslow" for now. Calls with family = "cox" that don’t set cox.ties emit a warning — the default switches to "efron" in v5.1 to match survival::coxph.

Algorithm control

  • New control = list(...) argument to glmnet() (and to cv.glmnet, glmnet.path, glmnet.fit, elnet.fit) overrides any of 17 algorithm-control parameters for a single call without mutating session state. Unknown keys error.
  • Top-level thresh, maxit, dfmax, pmax, trace.it in glmnet() are deprecated; use control = list(...) or glmnet.control().
  • dfmax and pmax signature defaults are now NULL, resolving at call time to nvars + 1 and min(2*dfmax + 20, nvars).

Vignettes

  • New glmnet-history.Rmd — package history, milestones, attributions.
  • New coxdev.Rmd — the coxdev deviance/gradient library.

Other behavior changes

  • predict.glmnet(type = "nonzero", s = ...) now always returns a list (one slot per s value, each slot an integer vector of active-coefficient indices). Earlier versions returned a data.frame when the per-s index counts happened to be uniform, and a list otherwise. This makes the return shape consistent with the no-s form and with the function’s documentation, but is a silent breaking change for callers that branched on is.data.frame() of the result. To get a stable union of indices across s values regardless of glmnet version, use sort(unique(unlist(predict(fit, type = "nonzero", s = lambda)))).

glmnet 4.1 Series

CRAN release: 2021-01-11

4.1-10 (2025-07-17)

Adjusted plotting again. Default is now using -log(lambda) as default for plotting, which is option xvar=‘lambda’. Also fixed labeling issues with predict and coef

4.1-9 (2025-06-02)

Changed default plotting xvar = “lambda”. Corrected some minor issues in citation file.

4.1-7 (2023-03-23)

Added DOI for JSS 2023 paper and corrected some typos in documentation (nfold -> nfolds) and vignette.

4.1-6 (2022-11-27)

Removed unneeded legacy fortran code, leaving only coxnet. Fixed up Matrix as() sequences

4.1-5

Relatively minor changes to bugs in survival functions and bigGlm, and some improved failure messages.

4.1-4 (2022-04-15)

Most of the Fortran code has been replaced by C++ by James Yang, leading to speedups in all cases. The exception is the Cox routine for right censored data, which is still under development.

4.1-3 (2021-11-02)

Some of the Fortran in glmnet has been replaced by C++, written by the newest member of our team, James Yang. * the wls routines (dense and sparse), that are the engines under the glmnet.path function when we use programmable families, are now written in C++, and lead to speedups of around 8x. * the family of elnet routines (sparse/dense, covariance/naive) for glmnet(...,family="gaussian") are all in C++, and lead to speedups around 4x.

4.1-2 (2021-06-24)

A new feature added, as well as some minor fixes to documentation. * The exclude argument has come to life. Users can now pass a function that can take arguments x, y and weights, or a subset of these, for filtering variables. Details in documentation and vignette. * Prediction with single newx observation failed before. This is fixed. * Labeling of predictions from cv.glmnet improved. * Fixed a bug in mortran/fortran that caused program to loop ad infinitum

4.1-1 (2021-02-21)

Fixed some bugs in the coxpath function to do with sparse X. * when some penalty factors are zero, and X is sparse, we should not call GLM to get the start * apply does not work as intended with sparse X, so we now use matrix multiplies instead in computing lambda_max * added documentation for cv.glmnet to explain implications of supplying lambda

4.1 (2021-01-11)

Expanded scope for the Cox model. * We now allow (start, stop) data in addition to the original right-censored all start at zero option. * Allow for strata as in survival::coxph * Allow for sparse X matrix with Cox models (was not available before) * Provide method for survival::survfit

Vignettes are revised and reorganized. Additional index information stored on cv.glmnet objects, and included when printed.

glmnet 4.0 Series

CRAN release: 2020-05-14

4.0-2 (2020-06-16)

  • Biggest change. Cindex and auc calculations now use the concordance function from package survival
  • Minor changes. Allow coefficient warm starts for glmnet.fit. The print method for glmnet now really prints %Dev rather than the fraction.

4.0 (2020-05-14)

Major revision with added functionality. Any GLM family can be used now with glmnet, not just the built-in families. By passing a “family” object as the family argument (rather than a character string), one gets access to all families supported by glm. This development was programmed by our newest member of the glmnet team, Kenneth Tay.

glmnet 3.0 Series

CRAN release: 2019-11-09

3.0-3

Bug fixes

  • Intercept=FALSE with “Gaussian” is fixed. The dev.ratio comes out correctly now. The mortran code was changed directly in 4 places. look for “standard”. Thanks to Kenneth Tay.

3.0-2 (2019-12-11)

Bug fixes

  • confusion.glmnet was sometimes not returning a list because of apply collapsing structure
  • cv.mrelnet and cv.multnet dropping dimensions inappropriately
  • Fix to storePB to avoid segfault. Thanks Tomas Kalibera!
  • Changed the help for assess.glmnet and cousins to be more helpful!
  • Changed some logic in lambda.interp to avoid edge cases (thanks David Keplinger)

3.0-1 (2019-11-15)

Minor fix to correct Depends in the DESCRIPTION to R (>= 3.6.0)

3.0 (2019-11-09)

This is a major revision with much added functionality, listed roughly in order of importance. An additional vignette called relax is supplied to describe the usage.

  • relax argument added to glmnet. This causes the models in the path to be refit without regularization. The resulting object inherits from class glmnet, and has an additional component, itself a glmnet object, which is the relaxed fit.
  • relax argument to cv.glmnet. This allows selection from a mixture of the relaxed fit and the regular fit. The mixture is governed by an argument gamma with a default of 5 values between 0 and 1.
  • predict, coef and plot methods for relaxed and cv.relaxed objects.
  • print method for relaxed object, and new print methods for cv.glmnet and cv.relaxed objects.
  • A progress bar is provided via an additional argument trace.it=TRUE to glmnet and cv.glmnet. This can also be set for the session via glmnet.control.
  • Three new functions assess.glmnet, roc.glmnet and confusion.glmnet for displaying the performance of models.
  • makeX for building the x matrix for input to glmnet. Main functionality is one-hot-encoding of factor variables, treatment of NA and creating sparse inputs.
  • bigGlm for fitting the GLMs of glmnet unpenalized.

In addition to these new features, some of the code in glmnet has been tidied up, especially related to CV.

glmnet 2.0 Series

2.0-20

  • Fixed a bug in internal function coxnet.deviance to do with input pred, as well as saturated loglike (missing) and weights
  • added a coxgrad function for computing the gradient

2.0-19

  • Fixed a bug in coxnet to do with ties between death set and risk set

2.0-18 (2019-05-20)

  • Added an option alignment to cv.glmnet, for cases when wierd things happen

2.0-17

  • Further fixes to mortran to get clean fortran; current mortran src is in inst/mortran

2.0-16 (2018-04-02)

  • Additional fixes to mortran; current mortran src is in inst/mortran
  • Mortran uses double precision, and variables are initialized to avoid -Wall warnings
  • cleaned up repeat code in CV by creating a utility function

2.0-15

  • Fixed up the mortran so that generic fortran compiler can run without any configure

2.0-13 (2017-09-22)

  • Cleaned up some bugs to do with exact prediction
  • newoffset created problems all over - fixed these

2.0-11

  • Added protection with exact=TRUE calls to coef and predict. See help file for more details

2.0-10 (2017-05-06)

  • Two iterations to fix to fix native fortran registration.

2.0-8 (2017-04-30)

  • included native registration of fortran

2.0-7

  • constant y blows up elnet; error trap included
  • fixed lambda.interp which was returning NaN under degenerate circumstances.

2.0-6

  • added some code to extract time and status gracefully from a Surv object

2.0-3 (2016-02-23)

  • changed the usage of predict and coef with exact=TRUE. The user is strongly encouraged to supply the original x and y values, as well as any other data such as weights that were used in the original fit.

2.0-1 (2015-04-08)

  • Major upgrade to CV; let each model use its own lambdas, then predict at original set.
  • fixed some minor bugs

glmnet 1.0 Series

1.9-9

  • fixed subsetting bug in lognet when some weights are zero and x is sparse

1.9-8 (2014-05-24)

  • fixed bug in multivariate response model (uninitialized variable), leading to valgrind issues
  • fixed issue with multinomial response matrix and zeros
  • Added a link to a glmnet vignette

1.9-6

  • fixed bug in predict.glmnet, predict.multnet and predict.coxnet, when s= argument is used with a vector of values. It was not doing the matrix multiply correctly
  • changed documentation of glmnet to explain logistic response matrix

1.9-5 (2013-08-04)

  • added parallel capabilities, and fixed some minor bugs

1.9-3 (2013-03-02)

  • added intercept option

1.9-1 (2013-02-10)

  • added upper and lower bounds for coefficients
  • added glmnet.control for setting systems parameters
  • fixed serious bug in coxnet

1.8-5 (2013-01-04)

  • added exact=TRUE option for prediction and coef functions

1.8 (2012-07-03)

  • Major new release
  • added mgaussian family for multivariate response
  • added grouped option for multinomial family

1.7-4 (2012-04-27)

  • nasty bug fixed in fortran - removed reference to dble
  • check class of newx and make dgCmatrix if sparse

1.7-1 (2011-09-23)

  • lognet added a classnames component to the object
  • predict.lognet(type="class") now returns a character vector/matrix

1.6 (2011-04-24)

  • predict.glmnet : fixed bug with type="nonzero"
  • glmnet: Now x can inherit from sparseMatrix rather than the very specific dgCMatrix, and this will trigger sparse mode for glmnet

1.5 (2010-11-04)

  • glmnet.Rd (lambda.min) : changed value to 0.01 if nobs < nvars, (lambda) added warnings to avoid single value, (lambda.min): renamed it lambda.min.ratio
  • glmnet (lambda.min) : changed value to 0.01 if nobs < nvars (HessianExact) : changed the sense (it was wrong), (lambda.min): renamed it lambda.min.ratio. This allows it to be called lambda.min in a call though
  • predict.cv.glmnet (new function) : makes predictions directly from the saved glmnet object on the cv object
  • coef.cv.glmnet (new function) : as above
  • predict.cv.glmnet.Rd : help functions for the above
  • cv.glmnet : insert drop(y) to avoid 1 column matrices; now include a glmnet.fit object for later predictions
  • nonzeroCoef : added a special case for a single variable in x; it was dying on this
  • deviance.glmnet : included
  • deviance.glmnet.Rd : included

1.4 (2010-06-16)

  • Note that this starts from version glmnet_1.4.