Model Overview

An R package which implements network event history analysis (NEHA).

• Jeffrey J. Harden, Bruce A. Desmarais, Mark Brockway, Frederick J. Boehmke, Scott J. LaCombe, Fridolin Linder, and Hanna Wallach. A Diffusion Network Event History Estimator. The Journal of Politics, Forthcoming

Installation

The package can be installed from CRAN.

install.packages("neha")

The latest development version can be installed from GitHub via devtools.

install.packages("devtools")

Now we can install from Github using the following line:

devtools::install_github("desmarais-lab/neha")

Example

library(neha)
# Simulate data for NEHA
# basic data parameters
cascades <- 50
nodes <- 20
times <- 30
nties <- 25
# generate dataframe
time <- sort(rep(1:times,nodes))
node <- paste("n",as.character(rep(1:nodes,times)),sep="")
intercept <- rep(1,length(time))
covariate <- runif(length(time))-2
data_for_sim <- data.frame(time,node,intercept,covariate,stringsAsFactors=F)

# regression parameters
beta <- cbind(c(-2.5,.25))
rownames(beta) <- c("intercept","covariate")

# generate network effects
possible_ties <- rbind(t(combn(1:nodes,2)),t(combn(1:nodes,2))[,c(2,1)])
possible_ties <- paste(paste("n",possible_ties[,1],sep=""),paste("n",possible_ties[,2],sep=""),sep="_")
ties <- sample(possible_ties,nties)
gamma <- cbind(rep(1.5,length(ties)))
rownames(gamma) <- ties

# initiate simulated data object
simulated_data <- NULL

# generate the data one cascade at a time
for(c in 1:cascades){
  simulated_cascade <- simulate_neha_discrete(x=data_for_sim,node="node",time="time",beta=beta,gamma=gamma,a=-6)
 simulated_cascade <- data.frame(simulated_cascade,cascade=c,stringsAsFactors=F)
  simulated_data <- rbind(simulated_data,simulated_cascade)
}

# estimate NEHA
neha_results <- neha(simulated_data,node="node",time="time",event="event",cascade="cascade",covariates="covariate",ncore=3)

# estimate NEHA logistic regression
neha_estimate <- glm(neha_results$combined_formula,data=neha_results$data_for_neha,family=binomial)
summary(neha_estimate)