## bigstatsr 1.2.2

• Function big_colstats() can now be run in parallel (added parameter ncores).

## bigstatsr 1.2.1

• It is now possible to use C++ FBM accessors without linking to {RcppArmadillo}.

## bigstatsr 1.2.0

• Functions big_(c)prodMat() and big_(t)crossprodSelf() now use much less memory, and may be faster.

• Add covar_from_df() to convert a data frame with factors/characters to a numeric matrix using one-hot encoding.

## bigstatsr 1.1.4

• Remove some ‘Suggests’ dependencies.

• Add a new column $all_conv to output of summary() for big_spLinReg() and big_spLogReg() to check whether all models have stopped because of “no more improvement”. Also add a new parameter sort to summary(). • Now warn (enabled by default) if some models may not have reached a minimum when using big_spLinReg() and big_spLogReg(). ## bigstatsr 1.1.1 • Fix In .self$nrow * .self$ncol : NAs produced by integer overflow. ## bigstatsr 1.1.0 • Make two different memory-mappings: one that is read-only (using $address) and one where it is possible to write (using $address_rw). This enables to use file permissions to prevent modifying data. • Also add a new field $is_read_only to be used to prevent modifying data (at least with <-) even when you have write permissions to it. Functions creating an FBM now gain a parameter is_read_only.

• Make vector accessors (e.g. X[1:10]) faster.

## bigstatsr 1.0.0

• Move some code to new packages {bigassertr} and {bigparallelr}.

• big_randomSVD() gains arguments related to matrix-vector multiplication.

• assert_noNA() is faster.

## bigstatsr 0.9.10

• Add big_increment().

## bigstatsr 0.9.9

In plot.big_SVD(),

• Can now plot many PCA scores (more than two) at once.

• Use coord_fixed() when plotting PCA scores because it is good practice.

• Use log-scale in scree plot to better see small differences in singular values.

• Reexport cowplot::plot_grid() to merge multiple ggplots.

## bigstatsr 0.9.6

• AUCBoot() is now 6-7 times faster.

## bigstatsr 0.9.5

• Add parameters center and scale to products.

## bigstatsr 0.9.3

• Fix a bug in big_univLogReg() for variables with no variation. IRLS was not converging, so glm() was used instead. The problem is that glm() drops dimensions causing singularities so that Z-score of the first covariate (or intercept) was used instead of a missing value.

## bigstatsr 0.9.0

• Use mio instead of boost for memory-mapping.

• Add a parameter base.row to predict.big_sp_list() and automatically detect if needed (as well as for covar.row).

• Possibility to subset a big_sp_list without losing attributes, so that one can access one model (corresponding to one alpha) even if it is not the ‘best’.

• Add parameters pf.X and pf.covar in big_sp***Reg() to provide different penalization for each variable (possibly no penalization at all).

## bigstatsr 0.8.4

Add %*%, crossprod and tcrossprod operations for ‘double’ FBMs.

## bigstatsr 0.8.3

Now also returns the number of non-zero variables ($nb_active) and the number of candidate variables ($nb_candidate) for each step of the regularization paths of big_spLinReg() and big_spLogReg().

## bigstatsr 0.8.0

• Parameters warn and return.all of big_spLinReg() and big_spLogReg() are deprecated; now always return the maximum information. Now provide two methods (summary and plot) to get a quick assessment of the fitted models.

## bigstatsr 0.7.3

• Check of missing values for input vectors (indices and targets) and matrices (covariables).

• AUC() is now stricter: it accepts only 0s and 1s for target.

## bigstatsr 0.7.1

• $bm() and $bm.desc() have been added in order to get an FBM as a filebacked.big.matrix. This enables using {bigmemory} functions.

## bigstatsr 0.7.0

• Type float added.

## bigstatsr 0.6.2

• big_write added.

## bigstatsr 0.6.1

• big_read now has a filter argument to filter rows, and argument nrow has been removed because it is now determined when reading the first block of data.

• Removed the save argument from FBM (and others); now, you must use FBM(...)\$save() instead of FBM(..., save = TRUE).

## bigstatsr 0.6.0

• You can now fill an FBM using a data frame. Note that factors will be used as integers.

• Package {bigreadr} has been developed and is now used by big_read.

## bigstatsr 0.5.0

• There have been some changes regarding how conversion between types is checked. Before, you would get a warning for any possible loss of precision (without actually checking it). Now, any loss of precision due to conversion between types is reported as a warning, and only in this case. If you want to disable this feature, you can use options(bigstatsr.downcast.warning = FALSE), or you can use without_downcast_warning() to disable this warning for one call.

## bigstatsr 0.4.1

• change big_read so that it is faster (corresponding vignette updated).

## bigstatsr 0.4.0

• possibility to add a “base predictor” for big_spLinReg and big_spLogReg.

• don’t store the whole regularization path (as a sparse matrix) in big_spLinReg and big_spLogReg anymore because it caused major slowdowns.

• directly average the K predictions in predict.big_sp_best_list.

• only use the “PSOCK” type of cluster because “FORK” can leave zombies behind. You can change this with options(bigstatsr.cluster.type = "PSOCK").

## bigstatsr 0.3.4

• Fix a bug in big_spLinReg related to the computation of summaries.

• Now provides function plus to be used as the combine argument in big_apply and big_parallelize instead of '+'.

## bigstatsr 0.3.3

• Before, this package used only the “PSOCK” type of cluster, which has some significant overhead. Now, it uses the “FORK” type on non-Windows systems. You can change this with options(bigstatsr.cluster.type = "PSOCK"). Uses “PSOCK” in 0.4.0.

## bigstatsr 0.3.2

• you can now provide multiple $$\alpha$$ values (as a numeric vector) in big_spLinReg and big_spLogReg. One will be chosen by grid-search.

## bigstatsr 0.3.1

• fixed a bug in big_prodMat when using a dimension of 1 or 0.

## bigstatsr 0.2.6

• no scaling is used by default for big_crossprod, big_tcrossprod, big_SVD and big_randomSVD (before, there was no default at all)

## bigstatsr 0.2.4

• Integrate Cross-Model Selection and Averaging (CMSA) directly in big_spLinReg and big_spLogReg, a procedure that automatically chooses the value of the $$\lambda$$ hyper-parameter.

• Speed up big_spLinReg and big_spLogReg (issue #12)

## bigstatsr 0.2.3

• Speed up AUC computations

## bigstatsr 0.2.0

• No longer use the big.matrix format of package bigmemory