Suggests: knitr, rmarkdown, testthat, devtools

Suggests: knitr, rmarkdown, testthat, devtools, vcr (>= 0.6.0)

Author: Annarosa Quarello [aut, cre], Emilie Lebarbier [aut], Olivier Bock [aut]
Description: Homogenize GNSS (Global Navigation Satellite System) time-series. The general model is a segmentation in the mean model including a periodic function and considering monthly variances,  see Quarello (2020) <arXiv:2005.04683>.

Title: Comprehensive GO Terms Comparison Between Species
Authors@R: c(person("Chrystian Camilo", "Sosa",role = c("aut","cre","cph"),
person("Diana Carolina", "Clavijo-Buriticá", role = "aut",
person("Mauricio Alberto", "Quimbaya",role = "aut",
person("Maria Victoria", "Diaz",role = "ctb",
person("Camila", "Riccio Rengifo",role = "ctb",
person("Arlen", "James Mosquera",role = "ctb",
Description: Supports the assessment of functional enrichment analyses obtained for several lists of genes and provides a workflow to analyze them between two species via weighted graphs. Methods are described in Sosa et al. (2022) (to be submitted).
Imports: base (>= 3.5), utils (>= 3.5), methods (>= 3.5), stats,
grDevices, ape, vegan, ggplot2, ggrepel, igraph, parallel,
Author: Chrystian Camilo Sosa [aut, cre, cph]
Maintainer: Chrystian Camilo Sosa <ccsosaa@javerianacali.edu.co>

Description: Supports the assessment of functional enrichment analyses obtained for several lists of genes and provides a workflow to analyze them between two species via weighted graphs. Methods are described in Sosa et al. (2022) (Submitted to Genomics).

Package: GOFSN
Type: Package
Title: Goodness-of-fit tests for the family of skew-normal models
Version: 1.0
Date: 2009-04-24
Author: Veronica Paton Romero
Maintainer: Veronica Paton Romero <v.paton@alumnos.urjc.es>
Depends: R (>= 2.10), sn
Description: GOFSN is a package that implements a method for checking
if a skew-normal model fits the observed dataset, when all
parameters are unknown. While location and scale parameters are
estimated by moment estimators, the shape parameter is
integrated with respect to the prior predictive distribution,
as proposed in (BOX, 1980). A default and proper prior on
skewness parameter is used to obtain the prior predictive
distribution, as proposed in (CABRAS, CASTELLANOS, 2008).
Goodness-of-fit tests, here proposed, depend only on sample
size and exhibit full agreement between nominal and actual
size. This package implements EDF statistics
Kolmogorov-Smirnov(D), Cram\'er-von Mises(W2) and proposes some
simple algorithms (SimulD,SimulW2) to approximate their
respective marginal predictive distributions. It also has
functions (ks.sn,W2.sn) that calculate the p-value on observed
data.
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2012-07-23 09:27:24 UTC; ripley
Repository: CRAN
Date/Publication: 2012-07-23 10:35:31