Variational Bayes (VB) Approximation of Gibbs Posteriors with
Hinge Losses
Variational Bayesian approximations of Gibbs measures with hinge losses for classification and ranking.

c(person("Michael", "Gruenstaeudl", role = c("aut", "cre"), email = "m.gruenstaeudl@fu-berlin.de"),
person("Nils", "Jenke", role = c("ctb"), email = "nilsj24@zedat.fu-berlin.de"))
Michael Gruenstaeudl [aut, cre],
Nils Jenke [ctb]
Visualizes the coverage depth of a complete plastid genome as well as the equality of its inverted repeat regions in relation to the circular, quadripartite genome structure and the location of individual genes. For more information, please see Gruenstaeudl and Jenke (2019) <doi:10.1101/697821>.

RCircos (>= 1.2.0), optparse (>= 1.6.0), genbankr (>= 1.2.1),
BiocGenerics (>= 0.20.0), Biostrings (>= 2.48.0),
GenomicAlignments (>= 1.18.1)

RCircos (>= 1.2.0), optparse (>= 1.6.0), genbankr (>= 1.2.1),
BiocGenerics (>= 0.20.0), Biostrings (>= 2.48.0),
GenomicAlignments (>= 1.18.1), GenomicRanges, IRanges
Visualizes the coverage depth of a complete plastid genome as well as the equality of its inverted repeat regions in relation to the circular, quadripartite genome structure and the location of individual genes. For more information, please see Gruenstaeudl and Jenke (2020) <doi:10.1186/s12859-020-3475-0>.

Nonparametric Estimation of Preferential Attachment and Node
Fitness in Temporal Complex Networks
Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
A statistically sound method for estimating jointly the attachment function and node fitness in a temporal complex network by maximizing a suitable penalized log-likelihood function is implemented in this package.

A statistically sound method for estimating jointly the attachment function and node fitness in a temporal complex network by maximizing a suitable penalized log-likelihood function is implemented in this package. Tutorial can be found in the accompanying vignette. More details about the method can be found at http://dx.doi.org/10.1371/journal.pone.0137796. To cite this package in your projects, please run the command: citation("PAFit") for a list of references you should cite.
Rcpp (>= 0.11.3) , grDevices, graphics, stats