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hawkesbow  

Estimation of Hawkes Processes from Binned Observations
View on CRAN: Click here


Download and install hawkesbow package within the R console
Install from CRAN:
install.packages("hawkesbow")

Install from Github:
library("remotes")
install_github("cran/hawkesbow")

Install by package version:
library("remotes")
install_version("hawkesbow", "1.0.3")



Attach the package and use:
library("hawkesbow")
Maintained by
Felix Cheysson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-03-31
Latest Update: 2024-01-12
Description:
Implements an estimation method for Hawkes processes when count data are only observed in discrete time, using a spectral approach derived from the Bartlett spectrum, see Cheysson and Lang (2020) . Some general use functions for Hawkes processes are also included: simulation of (in)homogeneous Hawkes process, maximum likelihood estimation, residual analysis, etc.
How to cite:
Felix Cheysson (2021). hawkesbow: Estimation of Hawkes Processes from Binned Observations. R package version 1.0.3, https://cran.r-project.org/web/packages/hawkesbow. Accessed 12 Jun. 2026.
Previous versions and publish date:
1.0.0 (2021-03-31 10:50), 1.0.1 (2021-04-07 11:20), 1.0.2 (2021-04-10 01:40)
Other packages that cited hawkesbow R package
View hawkesbow citation profile
Other R packages that hawkesbow depends, imports, suggests or enhances
Complete documentation for hawkesbow
Functions, R codes and Examples using the hawkesbow R package
Some associated functions: E1_imaginary . Etheta_imaginary . Exponential . Model . compensator . discrete . dpowerlaw . hawkes . hawkes_ogata . hawkesbow-package . inc_gamma_imag . inhpois . intensity . mle . plot.hawkes . plot.hawkes_ogata . plot.inhpois . residuals . whittle . 
Some associated R codes: RcppExports.R . discretize.R . hawkes.R . hawkes_ogata.R . hawkesbow-package.R . kernels.R . mle.R . powerlaw.R . whittle.R .  Full hawkesbow package functions and examples
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