| RHawkes-package {RHawkes} | R Documentation |
Renewal Hawkes Process
Description
The renewal Hawkes (RHawkes) process (Wheatley, Filimonov, and Sornette, 2016 <doi:10.1016/j.csda.2015.08.007>) 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) <doi:10.1080/10618600.2017.1341324>, 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) <doi:10.1007/s11222-021-10002-0> is also included.
Details
The DESCRIPTION file:
| Package: | RHawkes |
| Type: | Package |
| Title: | Renewal Hawkes Process |
| Version: | 1.0 |
| Date: | 2022-5-4 |
| Authors@R: | c(person(given="Feng", family="Chen", role = c("aut", "cre"), email = "feng.chen@unsw.edu.au", comment = c(ORCID="0000-0002-9646-3338") ), person(given="Tom", family="Stindl", role = "ctb", email="t.stindl@unsw.edu.au", comment=c(ORCID="0000-0001-8627-9337") ) ) |
| Description: | The renewal Hawkes (RHawkes) process (Wheatley, Filimonov, and Sornette, 2016 <doi:10.1016/j.csda.2015.08.007>) 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) <doi:10.1080/10618600.2017.1341324>, 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) <doi:10.1007/s11222-021-10002-0> is also included. |
| License: | GPL (>=2) |
| Depends: | R (>= 2.10), IHSEP |
| NeedsCompilation: | no |
| Author: | Feng Chen [aut, cre] (<https://orcid.org/0000-0002-9646-3338>), Tom Stindl [ctb] (<https://orcid.org/0000-0001-8627-9337>) |
| Maintainer: | Feng Chen <feng.chen@unsw.edu.au> |
Index of help topics:
EM1partial Partial EM algorithm for the RHawkes process,
version 1
EM2partial Partial EM algorithm for the RHawkes process,
version 2
RHawkes-package Renewal Hawkes Process
damllRH Dynamically approxomated minus loglikelihood of
a RHawkes model
mllRH Minus loglikelihood of a RHawkes model
mllRH1 Minus loglikelihood of a RHawkes model with
parent probabilities
mllRH2 Minus loglikelihood of a RHawkes model with
Rosenblatt residuals
pred.den RHawkes predictive density function
pred.haz RHawkes predictive hazard function
quake An RHawkes earthquake data set
sim.pred Simulate a fitted RHawkes process model
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
tms mid-price change times of the AUD/USD exchange
rate
Author(s)
NA
Maintainer: NA