https://github.com/sandialabs/stpphawkes

https://github.com/sandialabs/stpphawkes

scr-2937 snl-data-analysis

Last synced: 2 months ago
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• Host: GitHub
• URL: https://github.com/sandialabs/stpphawkes
• Owner: sandialabs
• License: other
• Created: 2023-08-03T03:29:00.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-03-10T22:11:11.000Z (over 1 year ago)
• Last Synced: 2026-02-15T21:16:23.479Z (5 months ago)
• Topics: scr-2937, snl-data-analysis
• Language: C++
• Homepage:
• Size: 190 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
stpphawkes R package

====================

*R library for spatio-temporal Hawkes process modeling with missing data*

[![R-CMD-check](https://github.com/sandialabs/stpphawkes/actions/workflows/r.yml/badge.svg)](https://github.com/sandialabs/stpphawkes/actions/workflows/r.yml)

[![CRAN status](https://www.r-pkg.org/badges/version/stpphawkes)](https://CRAN.R-project.org/package=stpphawkes)

A R package for modeling of spatio-temporal and temporal

point process using a Hawkes model accounting for missing 

data

### Installation

------------------------------------------------------------------------------

v0.2.2 is on [CRAN](https://cran.r-project.org/package=stpphawkes)

and can be installed as

> `install.packages("stpphawkes")`

1. Download zip or tar.gz of package or clone repository

2. Install into R (> 4.1.0)

> `install.packages("stpphawkes.tar.gz", repos = NULL)`

------------------------------------------------------------------------------

### References

J. D. Tucker, L. Shand, and J. R. Lewis, “Handling Missing Data in Self-Exciting Point Process Models,” Spatial Statistics, vol. 29. pp. 160-176, 2019. PDF