registry, settings, stringr, tibble, tikzDevice, magrittr,

Imports: forcats, fractional, glue, grDevices, Matrix, methods, POSetR,
R6, Rcpp, registry, settings, stringr, tibble, tikzDevice,

Provides support for building Feldman-Cousins confidence intervals
[G. J. Feldman and R. D. Cousins (1998) <doi:10.1103/PhysRevD.57.3873>].
Author: Valerio Gherardi [aut, cre] (<https://orcid.org/0000-0002-8215-3013>)

Depends: R (>= 2.15.1), glmnet, MASS, combinat
Description: Efficient procedures for community detection in network studies, especially for sparse networks with not very obvious community structure. The algorithms impose penalties on the differences of the coordinates which represent the community labels of the nodes.

person("Thomas","Willis", role = c("ctb", "aut")),
person("James", "Liley", role = c("ctb")))
Description: Provides functions to implement the Flexible cFDR (Hutchinson et al. (2021) <doi:10.1371/journal.pgen.1009853>) and Binary cFDR (Hutchinson et al. (2021) <doi:10.1101/2021.10.21.465274>) methodologies to leverage auxiliary data from arbitrary distributions, for example functional genomic data, with GWAS p-values to generate re-weighted p-values.
Imports: locfdr, MASS, ggplot2, cowplot, fields, dplyr, spatstat.geom,
polyCub, hexbin, bigsplines, data.table, grDevices, Hmisc
Suggests: stats, knitr, rmarkdown, digest, testthat (>= 3.0.0)
Author: Anna Hutchinson [aut, cre] (<https://orcid.org/0000-0002-9224-4410>),

Title: Forced Choice in Item Response Theory
Description: Bayesian estimation of forced choice models in Item Response Theory using 'rstan' (See Stan Development Team (2020) <https://mc-stan.org/>).
2.18.1), rstantools (>= 2.1.1), numDeriv
Author: Naidan Tu [aut, cre] (<https://orcid.org/0000-0002-5179-4133>),

Author: Paolo Giordani, Maria Brigida Ferraro
Description: Algorithms for fuzzy clustering and cluster validity indices
Packaged: 2014-03-26 11:22:48 UTC; Paolo Giordani

Description: Algorithms for fuzzy clustering and cluster validity

Description: Algorithms for fuzzy clustering, cluster validity indices and plots for cluster validity and visualizing fuzzy clustering results.