Package: hawkesbow 1.0.3
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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 11 months agofrom:7c6f8138cd. Checks:OK: 1 WARNING: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 08 2024 |
R-4.5-linux-x86_64 | WARNING | Dec 08 2024 |
Exports:compensatordiscretedpowerlawE1_imaginaryEtheta_imaginaryExponentialGaussianhawkeshawkes_ogatainc_gamma_imaginhpoisintensitymleModelPareto1Pareto2Pareto3PowerLawppowerlawqpowerlawresidualsrpowerlawSymmetricExponentialwhittle
Dependencies:BHnloptrRcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Compensator of a Hawkes process | compensator |
Discretizes a Hawkes simulation | discrete |
The power law distribution | dpowerlaw ppowerlaw qpowerlaw rpowerlaw |
Exponential integral of imaginary argument | E1_imaginary |
Incomplete gamma function of imaginary argument with arbitrary power | Etheta_imaginary |
Reproduction kernels for the Hawkes processes | Exponential Gaussian Pareto1 Pareto2 Pareto3 PowerLaw SymmetricExponential |
Simulation of a Hawkes process | hawkes |
Simulation of a Hawkes process | hawkes_ogata |
Incomplete gamma function of imaginary argument | inc_gamma_imag |
Simulation of an inhomogeneous Poisson process by thinning | inhpois |
Intensity of a Hawkes process | intensity |
Fitting Hawkes processes from continuous data | mle |
C++ abstract class for Hawkes processes | Model |
Plot of a Hawkes process | plot.hawkes |
Plot of a simulated Hawkes process | plot.hawkes_ogata |
Plot of a simulated inhomogeneous Poisson process | plot.inhpois |
Residuals of a Hawkes process | residuals |
Fitting Hawkes processes from discrete data | whittle |