GpGp
Fast Gaussian Process Computation Using Vecchia's Approximation
Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) http://www.jstor.org/stable/2345768, and the reordering and grouping methods are from Guinness (2018) doi:10.1080/00401706.2018.1437476. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) doi:10.48550/arXiv.1905.08374.
- Version0.5.1
- R version≥ 2.10
- LicenseMIT
- LicenseLICENSE
- Needs compilation?Yes
- Last release10/16/2024
Documentation
Team
Joseph Guinness
Matthias Katzfuss
Show author detailsRolesAuthorYoussef Fahmy
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 480 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 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 6,604 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Apr 15, 2024 with 82 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
- Imports2 packages
- Suggests5 packages
- Linking To3 packages
- Reverse Imports5 packages