lgcp
Log-Gaussian Cox Process
Spatial and spatio-temporal modelling of point patterns using the log-Gaussian Cox process. Bayesian inference for spatial, spatiotemporal, multivariate and aggregated point processes using Markov chain Monte Carlo. See Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J. Diggle (2015) doi:10.18637/jss.v063.i07.
- Version2.0
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- lgcp citation info
- Last release10/03/2023
Documentation
Team
Benjamin M. Taylor
Edzer Pebesma
Tilman M. Davies
Show author detailsRolesAuthorPeter J. Diggle
Show author detailsRolesAuthorBarry S. Rowlingson
Show author detailsRolesAuthorDominic Schumacher
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 842 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 13 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 12,869 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Feb 20, 2025 with 162 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports11 packages