Package: hawkesbow 1.0.3

Felix Cheysson

hawkesbow: Estimation of Hawkes Processes from Binned Observations

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) <arxiv:2003.04314>. Some general use functions for Hawkes processes are also included: simulation of (in)homogeneous Hawkes process, maximum likelihood estimation, residual analysis, etc.

Authors:Felix Cheysson [aut, cre]

hawkesbow_1.0.3.tar.gz
hawkesbow_1.0.3.tar.gz(r-4.5-noble)hawkesbow_1.0.3.tar.gz(r-4.4-noble)
hawkesbow_1.0.3.tgz(r-4.4-emscripten)hawkesbow_1.0.3.tgz(r-4.3-emscripten)
hawkesbow.pdf |hawkesbow.html
hawkesbow/json (API)

# Install 'hawkesbow' in R:
install.packages('hawkesbow', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cppopenmp

2.70 score 1 stars 4 scripts 225 downloads 24 exports 4 dependencies

Last updated 11 months agofrom:7c6f8138cd. Checks:OK: 1 WARNING: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 08 2024
R-4.5-linux-x86_64WARNINGDec 08 2024

Exports:compensatordiscretedpowerlawE1_imaginaryEtheta_imaginaryExponentialGaussianhawkeshawkes_ogatainc_gamma_imaginhpoisintensitymleModelPareto1Pareto2Pareto3PowerLawppowerlawqpowerlawresidualsrpowerlawSymmetricExponentialwhittle

Dependencies:BHnloptrRcppRcppArmadillo

hawkesbow

Rendered fromhawkesbow.Rmdusingknitr::rmarkdownon Dec 08 2024.

Last update: 2024-01-13
Started: 2021-03-31