rIsing: High-Dimensional Ising Model Selection

Fits an Ising model to a binary dataset using L1 regularized logistic regression and extended BIC. Also includes a fast lasso logistic regression function for high-dimensional problems. Uses the 'libLBFGS' optimization library by Naoaki Okazaki.

Install the latest version of this package by entering the following in R:
install.packages("rIsing")
AuthorPratik Ramprasad [aut, cre], Jorge Nocedal [ctb, cph], Naoaki Okazaki [ctb, cph]
Date of publication2016-11-25 08:43:07
MaintainerPratik Ramprasad <pratik.ramprasad@gmail.com>
LicenseGPL (>= 2)
Version0.1.0

View on CRAN

Files

src
src/misc.h
src/lbfgs
src/lbfgs/arithmetic_sse_double.h
src/lbfgs/arithmetic_ansi.h
src/lbfgs/lbfgs.c
src/lbfgs/arithmetic_sse_float.h
src/lbfgs/lbfgs.h
src/logreg.cpp
src/RcppExports.cpp
NAMESPACE
R
R/rIsing.R R/logreg.R R/RcppExports.R R/ising.R
MD5
DESCRIPTION
man
man/ising.Rd man/rIsing.Rd man/logreg.Rd

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