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hybridModels (version 0.3.7)

summary: summary for hybrid models

Description

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.

Usage

# S3 method for 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.

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>.

Examples

Run this code
# NOT RUN {
# 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))

# }

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