Bounded Memory Linear and Generalized Linear Models

Regression for data too large to fit in memory.


0.9 fix ODBC and DBI interfaces for bigglm to not use LIMIT, and just not allow variables to be floating free in the workspace (which really couldn't work anyway)

fix arguably-false-positive from Fortran bounds checking, by incorporating
the fix in the published AS274

0.8 allow offsets in model formulas for both biglm and bigglm.

0.7 Proper S4 inheritance for DBIConnection method. There's still something wrong with the set-up, since we have to export all the S3 methods for it to work.

summary.biglm object now has $nullrss, $rsq components

0.6 bigglm() now warns clearly when it runs out of iterations before convergence. (problem reported by Francisco J. Zagmutt)

0.5 SQLiteConnection method (RSQLite package) for bigglm.

biglm() no longer gives an error message when used on 
data of storage mode 'integer'

[The leaps package now has a regsubsets() method for biglm
objects (for Tal Galili).]

Sandwich variance estimates were wrong when weights were

predict() method and extractors for AIC, deviance, based
on code from Christophe Dutang

RODBC method (RODBC package) for bigglm

0.4 bigglm for glms.

0.3 Added sandwich estimator

0.2 Added weights

0.1 Initial version

Reference manual

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0.9-2.1 by Thomas Lumley, a year ago

Browse source code at

Authors: Thomas Lumley

Documentation:   PDF Manual  

Task views: High-Performance and Parallel Computing with R, Statistics for the Social Sciences

GPL license

Depends on DBI, methods

Suggests RSQLite, RODBC

Enhances leaps

Imported by cplm.

Depended on by biganalytics, rMR.

Suggested by DeclareDesign, broom, disk.frame, dynamichazard, emmeans, ff, ffbase, insight, ipumsr, leaps, optmatch.

Enhanced by prediction, texreg.

See at CRAN