Nothing
This package provides an R implementation of the netinf algorithm created by @gomez2010inferring (see here for more information and the original C++ implementation). Given a set of events that spread between a set of nodes the algorithm infers the most likely stable diffusion network that is underlying the diffusion process.
The package can be installed from CRAN:
install.packages("NetworkInference")
The latest development version can be installed from github:
#install.packages(devtools) devtools::install_github('desmarais-lab/NetworkInference')
To get started, get your data into the cascades
format required by the netinf
function:
library(NetworkInference) # Simulate random cascade data df <- simulate_rnd_cascades(50, n_node = 20) # Cast data into `cascades` object ## From long format cascades <- as_cascade_long(df) ## From wide format df_matrix <- as.matrix(cascades) ### Create example matrix cascades <- as_cascade_wide(df_matrix)
Then fit the model:
result <- netinf(cascades, quiet = TRUE, p_value_cutoff = 0.05)
head(result)
pander::pandoc.table(head(result))
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.