sis_apf: Fully adapted auxiliary Particle Filter for SIS model with...
In nianqiaoju/agents: Toolkit for inference in agent-based modelss

Fully adapted auxiliary Particle Filter for SIS model with Population Observation

1	sis_apf(y, model_config, particle_config)

y

a vector of length (T+1)

model_config

a list containing:

particle_config

a list containing:

'num_particles' : number of particles for the bootstrap particle filter
'ess_threshold' : if effective sample size drops below the threshold, then perform a resample step. ess_threshold = 1 means resampling at every step.
'save_particles': binary
'clock' : binary, default to FALSE. If clock = TRUE, then we will use a stopwatch to document its Sys.time()
'save_genealogy': binary
'verbose':
'exact': binary, if TRUE, then uses exact PoisBinom and exact CondBern, if FALSE then use translated Poisson and MCMC for CondBern. MUST HAVE!
'num_mcmc": required if exact = FALSE;

A list containing

'log_incremental_likelihood' :
'log_marginal_likelihood' :
'log_final_likelihood' :
'particles': [N, (T+1), num_particles] array storing the particles:
'eves' : the unique ancesters of each particle in the genealogy structure, if save_genealogy = TRUE;
'ess' : effective sample size at each step
'runtime' : elapse time at each step, if clock = TRUE;
'totaltime' : elapse time of running the whole particle filter, if clock = TRUE;