BinaryEMVS

Variable Selection for Binary Data Using the EM Algorithm

v0.1 · Jan 13, 2016 · GPL-3

Description

Implements variable selection for high dimensional datasets with a binary response variable using the EM algorithm. Both probit and logit models are supported. Also included is a useful function to generate high dimensional data with correlated variables.

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CRAN Check Status

13 OK

Show all 13 flavors

Flavor	Status	Time
r-devel-linux-x86_64-debian-clang	OK	37.4s
r-devel-linux-x86_64-debian-gcc	OK	26.6s
r-devel-linux-x86_64-fedora-clang	OK	60.8s
r-devel-linux-x86_64-fedora-gcc	OK	61.8s
r-devel-windows-x86_64	OK	68s
r-oldrel-macos-arm64	OK
r-oldrel-macos-x86_64	OK	60s
r-oldrel-windows-x86_64	OK	58s
r-patched-linux-x86_64	OK	36.3s
r-release-linux-x86_64	OK
r-release-macos-arm64	OK	13s
r-release-macos-x86_64	OK	63s
r-release-windows-x86_64	OK	60s

Check History

OK 12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 25, 2026

NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

NOTE r-oldrel-macos-arm64

LazyData

'LazyData' is specified without a 'data' directory

NOTE r-oldrel-macos-x86_64

LazyData

'LazyData' is specified without a 'data' directory

NOTE r-oldrel-windows-x86_64

LazyData

'LazyData' is specified without a 'data' directory

Version History

1 tracked

new 0.1 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Jan 13, 2016. Releases before tracking aren’t shown.