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RHawkes (version 1.0)

Renewal Hawkes Process

Description

The renewal Hawkes (RHawkes) process (Wheatley, Filimonov, and Sornette, 2016 ) is an extension to the classical Hawkes self-exciting point process widely used in the modelling of clustered event sequence data. This package provides functions to simulate the RHawkes process with a given immigrant hazard rate function and offspring birth time density function, to compute the exact likelihood of a RHawkes process using the recursive algorithm proposed by Chen and Stindl (2018) , to compute the Rosenblatt residuals for goodness-of-fit assessment, and to predict future event times based on observed event times up to a given time. A function implementing the linear time RHawkes process likelihood approximation algorithm proposed in Stindl and Chen (2021) is also included.

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Version

Install

install.packages('RHawkes')

Monthly Downloads

196

Version

1.0

License

GPL (>= 2)

Maintainer

Feng Chen

Last Published

May 5th, 2022

Functions in RHawkes (1.0)

EM1partial

Partial EM algorithm for the RHawkes process, version 1
damllRH

Dynamically approxomated minus loglikelihood of a RHawkes model
sim.pred

Simulate a fitted RHawkes process model
RHawkes-package

RHawkes
sim.pred1

Simulate a fitted RHawkes process model for prediction purposes
simRHawkes

Simulate a renewal Hawkes (RHawkes) process
simRHawkes1

Simulate a renewal Hawkes (RHawkes) process
pred.haz

RHawkes predictive hazard function
tms

mid-price change times of the AUD/USD exchange rate
quake

An RHawkes earthquake data set
mllRH1

Minus loglikelihood of a RHawkes model with parent probabilities
mllRH

Minus loglikelihood of a RHawkes model
mllRH2

Minus loglikelihood of a RHawkes model with Rosenblatt residuals
pred.den

RHawkes predictive density function
EM2partial

Partial EM algorithm for the RHawkes process, version 2