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
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hawkesbow_1.0.3.tgz(r-4.4-x86_64)hawkesbow_1.0.3.tgz(r-4.4-arm64)hawkesbow_1.0.3.tgz(r-4.3-x86_64)hawkesbow_1.0.3.tgz(r-4.3-arm64)
hawkesbow_1.0.3.tar.gz(r-4.5-noble)hawkesbow_1.0.3.tar.gz(r-4.4-noble)
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hawkesbow.pdf |hawkesbow.html✨
hawkesbow/json (API)
| # Install 'hawkesbow' in R: |
| install.packages('hawkesbow', repos = c('https://fcheysson.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/fcheysson/hawkesbow/issues
Last updated 11 months agofrom:3d4a29e94d. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-win-x86_64 | OK | Nov 23 2024 |
| R-4.5-linux-x86_64 | OK | Nov 23 2024 |
| R-4.4-win-x86_64 | OK | Nov 23 2024 |
| R-4.4-mac-x86_64 | OK | Nov 23 2024 |
| R-4.4-mac-aarch64 | OK | Nov 23 2024 |
| R-4.3-win-x86_64 | OK | Nov 23 2024 |
| R-4.3-mac-x86_64 | OK | Nov 23 2024 |
| R-4.3-mac-aarch64 | OK | Nov 23 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 |
