sodavis: SODA: Main and Interaction Effects Selection for Discriminant Analysis and Logistic Regression
Version 0.1

Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under quadratic discriminant analysis and logistic regression model.

AuthorYang Li, Jun S. Liu
Date of publication2015-11-16 08:20:20
MaintainerYang Li <yli01@fas.harvard.edu>
LicenseGPL-2
Version0.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("sodavis")

Popular man pages

soda: SODA algorithm for variable and interaction selection
soda_trace_CV: Calculate a trace of cross-validation error rate for SODA...
umich_lung: Gene expression data for Michigan lung cancer study in Beer...
See all...

All man pages Function index File listing

Man pages

soda: SODA algorithm for variable and interaction selection
soda_trace_CV: Calculate a trace of cross-validation error rate for SODA...
umich_lung: Gene expression data for Michigan lung cancer study in Beer...

Functions

calc_BIC Source code
calc_lda_BIC Source code
create_pmatrix_from_terms Source code
get_inter_terms_vec Source code
get_lin_terms Source code
get_lin_terms_vec Source code
get_quad_terms_vec Source code
get_set_from_terms Source code
get_term_name Source code
get_term_name_2 Source code
logistic_terms_CV Source code
mich_lung_xx Man page
mich_lung_yy Man page
nqnorm Source code
soda Man page Source code
soda_trace_CV Man page Source code
trim_terms Source code

Files

NAMESPACE
data
data/mich_lung.RData
data/datalist
R
R/pure_soda.R
MD5
DESCRIPTION
man
man/soda.Rd
man/soda_trace_CV.Rd
man/umich_lung.Rd
sodavis documentation built on May 19, 2017, 8:31 a.m.