Extract filtered trajectories from fitting a PMCMC algorithm

Extract filtered trajectories from a particle Markov chain Monte Carlo algorithm.

Usage

# S4 method for class 'SimInf_pmcmc'
trajectory(model, compartments, index, start = 1, end = NULL, thin = 1)

Arguments

model

the SimInf_pmcmc object to extract the filtered trajectories from.

compartments

specify the names of the compartments to extract data from. The compartments can be specified as a character vector e.g. compartments = c('S', 'I', 'R'), or as a formula e.g. compartments = ~S+I+R (see ‘Examples’). Default (compartments=NULL) is to extract the number of individuals in each compartment i.e. the data from all discrete state compartments in the model. In models that also have continuous state variables e.g. the SISe model, they are also included.

index

indices specifying the subset of nodes to include when extracting data. Default (index = NULL) is to extract data from all nodes.

start

The start iteration to remove some burn-in iterations. Default is start = 1.

end

the last iteration to include. Default is NULL which set end to the last iteration in the chain.

thin

keep every thin iteration after the start iteration. Default is thin = 1, i.e., keep every iteration.

Value

A data.frame where the first column is the iteration and the remaining columns are the result from calling trajectory,SimInf_model-method with the arguments compartments and index for each iteration.