saom_simulate: Function for simulating from a stochastic actor-oriented...

In sctyner/netvizinf: Create network lineups for visual inference on stochastic actor-oriented models

Description

Function for simulating from a stochastic actor-oriented model.

Usage

saom_simulate(dat, struct, parms, N)

Arguments

dat	A Siena data object. For more information see ?RSiena::sienaDataCreate
struct	A Siena effects structure object. Include all effects you wish to include in the model. See ?RSiena::getEffects for more.
parms	Numeric vector of effects. The rate parameters must be listed first, followed by the effects in the objective function.
N	Integer. Number of simulations you desire from the model.

Examples

## Not run: 
# data set up from \url{https://www.stats.ox.ac.uk/~snijders/siena/basicRSiena.r}
library(RSiena)
friend.data.w1 <- as.matrix(read.table("data/s50-network1.dat"))
friend.data.w2 <- as.matrix(read.table("data/s50-network2.dat"))
friend.data.w3 <- as.matrix(read.table("data/s50-network3.dat"))
drink <- as.matrix(read.table("data/s50-alcohol.dat"))
friendshipData <- array(c(friend.data.w1, friend.data.w2, friend.data.w3), dim = c(50, 50, 3))
friendship <- sienaDependent(friendshipData)
alcohol <- varCovar(drink)
mydata <- sienaDataCreate(friendship, alcohol)
M1eff <- getEffects(mydata)
load("data/M1ests_bigfriends.rda")
M1parms <- colMeans(M1ests_bigfriends)
M1sims5 <- saom_simulate(dat = mydata, struct = M1eff,
                       parms = M1parms, N = 5)

## End(Not run)

sctyner/netvizinf documentation built on May 29, 2019, 4:20 p.m.