Title: Discrimination/Classification in very high dimension with linear
Description: This package provides an implementation of Linear
disciminant analysis and quadratic discriminant analysis that
works fine in very high dimension (when there are many more
Packaged: 2010-05-02 07:12:59 UTC; robingirard

Description: This package provides an implementation of Linear discriminant analysis and quadratic discriminant analysis that works fine in very high dimension (when there are many more variables than observations).
Packaged: 2013-12-11 14:42:03 UTC; robin.girard

major river basins around the world, as well as globally
References: "Liang, X., D. P. Lettenmaier, E. F. Wood, and

Title: VIF Regression: A Fast Regression Algorithm For Large Data
Description: This package implements a fast regression algorithm for
building linear model for large data as defined in the paper
"VIF-Regression: A Fast Regression Algorithm for Large Data
(2009)" by Dongyu Lin, Dean P. Foster and Lyle H. Ungar.

Packaged: Mon Sep 28 17:40:20 2009; dongyu

(2011), Journal of the American Statistical Association, Vol.
106, No. 493: 232-247" by Dongyu Lin, Dean P. Foster, and Lyle

Title: Detecting Change-Points via VIFCP Method
Author: Xiaoping shi, Xiangsheng Wang, Dongwei Wei, Yuehua Wu
Description: Contains a function to support the paper 'A sequential multiple change-point detection
procedure via VIF regression' (in print).

Author: Xiaoping Shi, Xiangsheng Wang, Dongwei Wei, Yuehua Wu
procedure via VIF regression' (Accepted by Computational Statistics).

Description: Contains a function to support the following paper:
Xiaoping Shi, Xiang-Sheng Wang, Dongwei Wei, Yuehua Wu (2016), <DOI:10.1007/s00180-015-0587-5>,
A sequential multiple change-point detection procedure via VIF regression,

Title: Variational Bayesian Inference for Genome-Wide Regression
Authors@R: c(person("Akio", "Onogi", role = c("aut", "cre", "cph"), email = "onogiakio@gmail.com"), person("R Core Team", role = "ctb", comment = "Provide Rdynload.h and Boolean.h"), person("Hiroyoshi", "Iwata", role = "cph"), person("Takuji", "Nishimura", role = "ctb", comment = "Developer of Mersenne twister in header1.h"), person("Makoto", "Matsumoto", role = "ctb", comment = "Developer of Mersenne twister in header1.h"), person("STRUCTURE software contributors", role = "ctb", comment="Provide snorm and RNormal functions in header2.h"), person("Alan", "Miller", role = "ctb", comment = "Program mylgamma function in header2.h"), person("Peter", "Beerli", role = "ctb", comment = "Translate mylgamma function in header2.h"))
Description: Conducts linear regression using variational Bayesian inference, particularly optimized for genome-wide association mapping and whole-genome prediction which use a number of DNA markers as the explanatory variables. Provides seven regression models which select the important variables (i.e., the variables related to response variables) among the given explanatory variables in different ways (i.e., model structures).
R Core Team [ctb] (Provide Rdynload.h and Boolean.h),
Takuji Nishimura [ctb] (Developer of Mersenne twister in header1.h),
Makoto Matsumoto [ctb] (Developer of Mersenne twister in header1.h),
STRUCTURE software contributors [ctb] (Provide snorm and RNormal
Alan Miller [ctb] (Program mylgamma function in header2.h),
Peter Beerli [ctb] (Translate mylgamma function in header2.h)