/HawkesCausalInfection

Using Hawkes Processes to Identify Cases inInfectious Disease Outbreaks with No KnownCausal Infection

Primary LanguageRMIT LicenseMIT

HawkesCausalInfection

Using Hawkes Processes to identify cases in infectious disease outbreaks with no known causal infection

Cluster based simulation of a Hawkes process done using Simulation_Cluster.R.

Inputs: Events - any events at time 0 (vector) T_max - maximum time of simulation (float) N_max - maximum number of events used as a safety in case of especially long runs. Should be specified higher than anticipated need. (integer) mu_fn - the background intensity to be simulated from. Use one of Background_Intensities.R (function) phi_fn - the triggering function to use. Use one of Kernel_Times.R (function) branching_factor - the branching factor of the chosen triggering function. Use one of Branching_Factors.R (function) parameters - the parameters of the process to be simulated from. To be user specified (list)

EM for Rayleigh kernel and Exponential kernel can be done using their specific code options.

Inputs: starting_values - initial values of parameters of process (list) times - time points of point process to be estimated (vector) T_max - maximum time point of process (float) thresh - threshold of sensitivity of process. 1e-4 often used. (float)