summary function

summary for hybrid models

summary.HM is a method to print a summary with basic description of nodes' states at a specific time (the time must be present in the network data). The default value is Null, that means it prints nodes' final states.

## S3 method for class 'HM'
summary(object, at = NULL, stateVars = NULL, nodes = NULL, ...)

Arguments

• object: HM object
• at: the date (as character) that will be used to print the summary
• stateVars: vector containing the state variable to summarize. The default value is NULL, which will print a summary with all states.
• nodes: vector containing the nodes of interest. The default value is NULL, which will print a summary with all nodes.
• ...: arguments to be passed to methods.

Examples

# Parameters and initial conditions for an SIS model
# loading the data set 
data(networkSample) # help("networkSample"), for more info
networkSample <- networkSample[which(networkSample$Day < "2012-03-20"),]

var.names <- list(from = 'originID', to = 'destinationID', Time = 'Day',
                  arc = 'num.animals')
                  
prop.func <- c('beta * S * I / (S + I)', 'gamma * I')
state.var <- c('S', 'I')
state.change.matrix <- matrix(c(-1,  1,  # S
                                 1, -1), # I
                              nrow = 2, ncol = 2, byrow = TRUE)
                              
model.parms <- c(beta = 0.1, gamma = 0.01)

init.cond <- rep(100, length(unique(c(networkSample$originID,
                                      networkSample$destinationID))))
names(init.cond) <- paste('S', unique(c(networkSample$originID,
                                        networkSample$destinationID)), sep = '')
init.cond <- c(init.cond, c(I36811 = 10, I36812 = 10)) # adding infection
                  
# running simulations, check num of cores available (num.cores)
sim.results <- hybridModel(network = networkSample, var.names = var.names,
                           model.parms = model.parms, state.var = state.var,
                           prop.func = prop.func, init.cond = init.cond,
                           state.change.matrix = state.change.matrix,
                           sim.number = 4, num.cores = 2)

summary(sim.results, stateVars = c('S', 'I'), nodes = c(36812, 36813))

References

[1] Fernando S. Marques, Jose H. H. Grisi-Filho, Marcos Amaku et al. hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Network. In: Jounal of Statistical Software Volume 94, Issue 6 doi:10.18637/jss.v094.i06.