Package: DCEM
Type: Package
Title: Clustering Big Data using Expectation Maximization Star (EM*)
        Algorithm
Version: 2.0.6
Authors@R: c(
    person("Sharma", "Parichit", email = "parishar@iu.edu", role = c("aut","cre", "ctb")),
    person("Kurban", "Hasan", role = c("aut","ctb")),
    person("Dalkilic", "Mehmet", role = "aut")) 
Maintainer: Sharma Parichit <parishar@iu.edu>
Description: Implements the Improved Expectation Maximisation EM* and the traditional EM algorithm for clustering 
    big data (gaussian mixture models for both multivariate and univariate datasets). This version 
    implements the faster alternative-EM* that expedites convergence via structure based data segregation. 
    The implementation supports both random and K-means++ based initialization. Reference: Parichit Sharma, 
    Hasan Kurban, Mehmet Dalkilic (2022) <doi:10.1016/j.softx.2021.100944>. Hasan Kurban, 
    Mark Jenne, Mehmet Dalkilic (2016) <doi:10.1007/s41060-017-0062-1>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: mvtnorm (>= 1.0.7), matrixcalc (>= 1.0.3), MASS (>= 7.3.49),
        Rcpp (>= 1.0.2)
LinkingTo: Rcpp
RoxygenNote: 7.1.2
Depends: R(>= 3.2.0)
URL: https://github.com/parichit/DCEM
BugReports: https://github.com/parichit/DCEM/issues
Suggests: knitr, rmarkdown, spelling
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: yes
Packaged: 2026-04-13 21:55:17 UTC; parichit
Author: Sharma Parichit [aut, cre, ctb],
  Kurban Hasan [aut, ctb],
  Dalkilic Mehmet [aut]
Repository: CRAN
Date/Publication: 2026-04-14 07:10:07 UTC
Built: R 4.5.2; aarch64-apple-darwin20; 2026-04-15 04:54:43 UTC; unix
Archs: DCEM.so.dSYM
