Authors@R: person("Kevin", "Kuo", email = "kevin.kuo@rstudio.com",
Description: A 'sparklyr' <https://spark.rstudio.com/> extension that provides an R
interface for 'GraphFrames' <https://graphframes.github.io/>. 'GraphFrames' is a package
for 'Apache Spark' that provides a DataFrame-based API for working with graphs. Functionality
includes motif finding and common graph algorithms, such as PageRank and Breadth-first
Packaged: 2018-04-05 14:36:05 UTC; kevinykuo

Packaged: 2018-06-21 05:41:10 UTC; kevinykuo

Packaged: 2018-10-30 19:01:05 UTC; kevinykuo

Title: An R Interface to the 'GraphHopper' Directions API
Authors@R: person("Stefan", "Kuethe", role = c("aut", "cre"), email = "crazycapivara@gmail.com")
Description: Provides a quick and easy access to the 'GraphHopper' Directions API.
'GraphHopper' <https://www.graphhopper.com/> itself is a routing engine based on 'OpenStreetMap' data.
API responses can be converted to simple feature (sf) objects in a convenient way.
Imports: magrittr, httr, googlePolylines, jsonlite, tibble, dplyr

Suggests: sf, geojsonsf, ggplot2, testthat

Title: Statistical Methodology for Graphical Extreme Value Models
person("Sebastian", "Engelke", email = "sebastian.engelke@unige.ch",
person("Adrien S.", "Hitz", role = "aut"),
person("Nicola", "Gnecco", role = "aut"))
Description: Statistical methodology for sparse multivariate extreme value models. Methods are
provided for exact simulation and statistical inference for multivariate Pareto distributions
on graphical structures as described in the paper 'Graphical Models for Extremes' by
Imports: igraph (>= 1.2.4.1), mvtnorm (>= 1.0.10), matrixcalc (>=

Title: Graphical VAR for Experience Sampling Data
Description: Estimates within and between time point interactions in experience sampling data, using the Graphical VAR model in combination with LASSO and EBIC.
Imports: Rcpp (>= 0.11.3), Matrix, glasso, glmnet, mvtnorm, qgraph (>=

Packaged: 2016-07-02 20:54:55 UTC; sachaepskamp

Packaged: 2017-09-06 13:49:25 UTC; sachaepskamp

Description: Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Packaged: 2018-06-16 13:50:55 UTC; sachaepskamp