convoSPAT
Convolution-Based Nonstationary Spatial Modeling
Fits convolution-based nonstationary Gaussian process models to point-referenced spatial data. The nonstationary covariance function allows the user to specify the underlying correlation structure and which spatial dependence parameters should be allowed to vary over space: the anisotropy, nugget variance, and process variance. The parameters are estimated via maximum likelihood, using a local likelihood approach. Also provided are functions to fit stationary spatial models for comparison, calculate the Kriging predictor and standard errors, and create various plots to visualize nonstationarity.
- Version1.2.7
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- convoSPAT citation info
- Last release01/16/2021
Team
Mark D. Risser
Insights
Last 30 days
This package has been downloaded 232 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 3,512 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 21, 2024 with 158 downloads.
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Dependencies
- Imports5 packages