Title: Time Series Modeling for Climate Change Proxies
Description: Implementation of the Wilkinson and Ivany (2002) approach to paleoclimate analysis, applied to isotope data extracted from clams.

Title: Classes and Methods for "Class Comparison" Problems on
Description: Defines the classes used for "class comparison" problems
in the OOMPA project (<http://oompa.r-forge.r-project.org/>). Class
comparison includes tests for differential expression; see Simon's
book for details on typical problem types.
Imports: methods, graphics, stats, splines, Biobase

Packaged: 2019-05-06 12:39:50 UTC; Kevin Coombes

Title: Classes and Methods for "Class Discovery" with Microarrays or
Depends: R (>= 3.0), cluster, oompaBase (>= 3.0.1)
Imports: methods, stats, graphics, grDevices, mclust, oompaData,
Description: Defines the classes used for "class discovery" problems
discovery primarily consists of unsupervised clustering methods with
attempts to assess their statistical significance.

Packaged: 2019-05-06 12:43:58 UTC; Kevin Coombes

Author: Florencia I. Pozzi, Gisela Y. Green, Ivana G. Barbona, Gustavo R. Rodriguez, Silvina A. Felitti
Maintainer: Florencia I. Pozzi <florenciapoz@hotmail.com>
Description: Cleans biological sequences massively, quickly, without errors and
without internet connection.  Biological sequences cleaning is performed by
aligning the forward and / or revers primers or ends of cloning vectors with the sequences
to be cleaned. After the alignment, new subsequences are generated without biological fragment
Packaged: 2018-05-09 17:39:40 UTC; Florencia Pozzi

Author: Florencia I. Pozzi, Silvina A. Felitti
Description: Curates biological sequences massively, quickly, without errors and
without internet connection.  Biological sequences curing is performed by
Packaged: 2022-04-27 17:08:53 UTC; Florencia

Title: Model-Based Clustering of Categorical Sequences
Authors@R: c(person("Volodymyr", "Melnykov", role = c("aut", "cre"), email =
Description: ClickClust allows clustering categorical sequences by means of finite mixtures with Markov model components. ClickClust also allows detecting blocks of equivalent states by forward and backward state selection procedures.