README.md

In HanjoStudy/VineVizR: Basic integration of VizNetworks with VineCopula

VineVizR

A package to visualise RVineMatrix objects with visNetwork

Installation

Install the VineVizR package from inside R using the devtools library

library(devtools)
install_gtithub("HanjoStudy/VineVizR")
library(VineVizR)

After packge has succesfully installed, we need to load the libraries that the function will need to generate the network. You can use the helper function load_pkg to load all the package. If the package is not installed, this function will install it and then load the library. The package also contain some data that should help illustrate the function use

load_pkg(c("dplyr", "visNetwork", "tidyr", "VineCopula"))
data("RVM")
data("Market_info")

Now that the packages have been loaded along with the RVineMatrix and some market information, we now generate a group that is formed using the my industry groupings from the Market_Info dataset

group <- Market_info$Hanjo.Industry %>% as.character()
group.size <-  
  Market_info %>% 
  group_by(Hanjo.Industry) %>%
  summarise(n = n()) %>% 
  select(n) %>% unlist 

colours <- c("#39c9bb", "#398fc9", "#39c973"," #bb39c9",    "#c9bb39")
 ```
 After you set the groupings, the group sizes and any of the other optional parameters, the function can now be run
 ```r
 VisVineR(
  RVM,
  group = group,
  group.size = group.size,
  colours = colours,
  shape = "circle",
  seed = 50)

Enjoy the interactive display!

HanjoStudy/VineVizR documentation built on May 6, 2019, 10:55 p.m.