linear regression for data too large to fit in memory

bounded memory linear and generalized linear models
Regression for data too large to fit in memory

Bounded Memory Linear and Generalized Linear Models
Regression for data too large to fit in memory.

c(person(given="Thomas", family="Lumley", email="tlumley@u.washington.edu", role="aut"), person(given="Christophe", family="Dutang", email="christophe.dutang@ensimag.fr", role="ctb"), person(given="Alan", family="Miller", role="ctb", comment="Algorithm AS 274"), person(given="Morven", family="Gentleman", role="ctb", comment="Algorithm AS 75"), person(given="Mark", family="Purver", email="mark_purver@hotmail.com", role="cre"))
Thomas Lumley [aut],
Christophe Dutang [ctb],
Alan Miller [ctb] (Algorithm AS 274),
Morven Gentleman [ctb] (Algorithm AS 75),
Mark Purver [cre]
Regression for data too large to fit in memory. This package functions exactly like the 'biglm' package, but works with later versions of R.

Making Optimal Matching Size-Scalable Using Optimal Calipers
Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists.
Glover, F. (1967).  <DOI:10.1002/nav.3800140304>.
Katriel, I. (2008). <DOI:10.1287/ijoc.1070.0232>.
Rosenbaum, P.R. (1989). <DOI:10.1080/01621459.1989.10478868>.
Yang, D., Small, D. S., Silber, J. H., and Rosenbaum, P. R. (2012). <DOI:10.1111/j.1541-0420.2011.01691.x>.
rcbalance, stats, liqueueR, plyr, mvnfast

Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists. The main functions in the bigmatch package are optcal() to find the optimal caliper and nfmatch() to find a near-fine balance match with a caliper.
Glover, F. (1967).  <DOI:10.1002/nav.3800140304>.
Katriel, I. (2008). <DOI:10.1287/ijoc.1070.0232>.
Rosenbaum, P.R. (1989). <DOI:10.1080/01621459.1989.10478868>.
Yang, D., Small, D. S., Silber, J. H., and Rosenbaum, P. R. (2012). <DOI:10.1111/j.1541-0420.2011.01691.x>.