Package: clickb
Title: Web Data Analysis by Bayesian Mixture of Markov Models
Version: 0.1
Authors@R: 
    c(person("Furio", "Urso", email = "furio.urso@unipa.it", 
  role = c("aut", "cre")),person("Reza", "Mohammadi", email = "a.mohammadi@uva.nl", 
  role = "aut"),person("Antonino", "Abbruzzo", email = "antonino.abbruzzo@unipa.it", 
  role = "aut"),person("Maria Francesca", "Cracolici", email = "mariafrancesca.cracolici@unipa.it", 
  role = "aut"))
Description: Designed for web usage data analysis, it implements tools to process web sequences and identify web browsing profiles through sequential classification. Sequences' clusters are identified by using a model-based approach, specifically mixture of discrete time first-order Markov models for categorical web sequences. A Bayesian approach is used to estimate model parameters and identify sequences classification as proposed by Fruehwirth-Schnatter and Pamminger (2010) <doi:10.1214/10-BA606>.
License: MIT + file LICENSE
Imports: DiscreteWeibull, mclust, MCMCpack, parallel
Suggests: seqHMM
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2023-02-11 14:19:32 UTC; furio
Author: Furio Urso [aut, cre],
  Reza Mohammadi [aut],
  Antonino Abbruzzo [aut],
  Maria Francesca Cracolici [aut]
Maintainer: Furio Urso <furio.urso@unipa.it>
Repository: CRAN
Date/Publication: 2023-02-13 09:20:10 UTC
Built: R 4.6.0; ; 2026-04-26 06:29:52 UTC; unix
