pp_simulate: Simulate events from a temporal point process

In OwenWard/ppdiag: Diagnosis and Visualizations Tools for Temporal Point Processes

Simulate events from a temporal point process

Description

Currently available point processes are homogeneous Poisson, Hawkes with exponential kernel, MMHP and MMPP

Usage

pp_simulate(object, start = 0, end = 1, n = NULL, verbose = FALSE)

## Default S3 method:
pp_simulate(object, start = 0, end = 1, n = NULL, verbose = FALSE)

## S3 method for class 'hpp'
pp_simulate(object, start = 0, end = 1, n = NULL, verbose = FALSE)

## S3 method for class 'hp'
pp_simulate(object, start = 0, end = 1, n = NULL, verbose = FALSE)

## S3 method for class 'mmpp'
pp_simulate(object, start = 0, end = 1, n = NULL, verbose = FALSE)

## S3 method for class 'mmhp'
pp_simulate(object, start = 0, end = 1, n = NULL, verbose = FALSE)

Arguments

object	point process model object of type hpp, hp, mmhp, or mmpp
start	start time of events simulated. Not used for Markov modulated models
end	end time of events simulated. Not used for Markov modulated models
n	number of events simulated. Required for Markov modulated models, optional otherwise
verbose	whether to output informative messages as running

Value

a vector of event times for all models. For Markov modulated models, also returns details on the underlying latent process

Examples

hpp_obj <- pp_hpp(lambda = 1)
s <- pp_simulate(hpp_obj, n = 50)

OwenWard/ppdiag documentation built on Feb. 19, 2023, 11:34 a.m.