glmnet 4.1-7

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

glmnet 4.1-6

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

glmnet 4.1-5

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

glmnet 4.1-4

Most of the Fortran code has been replaced by C++ by James Yang, leading to speedups in all cases.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.

glmnet 4.1-3

Some of the Fortran in glmnet has been replaced by C++, written by the newest member of our team, James Yang.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.

glmnet 4.1-2

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

glmnet 4.1-1

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

glmnet 4.1

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 4.0-2

• 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.

glmnet 4.0

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 3.0-3

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.

glmnet 3.0-2

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)

glmnet 3.0-1

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

glmnet 3.0

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 2.0-20

• 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

glmnet 2.0-19

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

glmnet 2.0-18

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

glmnet 2.0-17

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

glmnet 2.0-16

• 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

glmnet 2.0-15

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

glmnet 2.0-13

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

glmnet 2.0-11

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

glmnet 2.0-10

• Two iterations to fix to fix native fortran registration.

glmnet 2.0-8

• included native registration of fortran

glmnet 2.0-7

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

glmnet 2.0-6

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

glmnet 2.0-3

• 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.

glmnet 2.0-1

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

glmnet 1.9-9

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

glmnet 1.9-8

• 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

glmnet 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

glmnet 1.9-5

• added parallel capabilities, and fixed some minor bugs

glmnet 1.9-3

• added intercept option

glmnet 1.9-1

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

glmnet 1.8-5

• added exact=TRUE option for prediction and coef functions

glmnet 1.8

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

glmnet 1.7-4

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

glmnet 1.7-1

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

glmnet 1.6

• 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

glmnet 1.5

• 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

glmnet 1.4

• Note that this starts from version glmnet_1.4.