Successive Over-Relaxation and SSOR methods. Nonstationary, also known as
Krylov subspace methods are also provided. Sparse matrix computation is also supported
LinkingTo: bigmemory, BH, Rcpp, RcppArmadillo

Authors@R: person("Kisung", "You", email = "kyou@nd.edu", role = c("aut", "cre"),comment=c(ORCID="0000-0002-8584-459X"))
Imports: Rcpp (>= 0.12.4), Matrix, Rdpack

Authors@R: person("Kisung", "You", email = "kyou@nd.edu", role = c("aut", "cre"), comment=c(ORCID="0000-0002-8584-459X"))

Authors@R: person("Kisung", "You", email = "kyoustat@gmail.com", role = c("aut", "cre"), comment=c(ORCID="0000-0002-8584-459X"))
Imports: Rcpp (>= 0.12.4), Matrix, Rdpack, stats, utils

Authors@R: person("Kisung", "You", email = "kisungyou@outlook.com", role = c("aut", "cre"), comment=c(ORCID="0000-0002-8584-459X"))

Package: Rlof
Version: 1.0.0
Date: 2011-10-07
Title: R parallel implementation of Local Outlier Factor(LOF)
Author: Yingsong Hu, Wayne Murray and Yin Shan with Strategic Data
Mining Team, Department of Human Services, Australian.
Maintainer: Yingsong Hu <yingsonghu@hotmail.com>
Depends: R (>= 2.12.0), doMC, foreach
Description: R parallel implementation of Local Outlier Factor(LOF)
which uses multiple cpus to significantly speed up the LOF
computation for large datasets. (Note: The overall performance
depends on the computers especially the number of the cores).
It also supports multiple k values to be calculated in
parallel, as well as various distance measures in addition to
the default Euclidean distance.
License: GPL (>= 2)
Packaged: 2011-10-07 06:20:25 UTC; yingsonghu
Repository: CRAN
Date/Publication: 2011-10-08 06:43:11

Title: R Parallel Implementation of Local Outlier Factor(LOF)
Author: Yingsong Hu, Wayne Murray and Yin Shan, Australia.
Depends: R (>= 2.14.0), doParallel, foreach
Description: R parallel implementation of Local Outlier Factor(LOF) which uses multiple CPUs to significantly speed up the LOF computation for large datasets. (Note: The overall performance depends on the computers especially the number of the cores).It also supports multiple k values to be calculated in parallel, as well as various distance measures in addition to the default Euclidean distance.
Packaged: 2015-09-11 00:26:26 UTC; yingsonghu