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
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Last 30 days
This package has been downloaded 434 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.
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Last 365 days
This package has been downloaded 6,576 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.
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Dependencies
- Imports2 packages
- Suggests5 packages
- Linking To3 packages
- Reverse Imports5 packages