Package: cocons 0.1.4
Federico Blasi
cocons: Covariate-Based Covariance Functions for Nonstationary Spatial Modeling
Estimation, prediction, and simulation of nonstationary Gaussian process with modular covariate-based covariance functions. Sources of nonstationarity, such as spatial mean, variance, geometric anisotropy, smoothness, and nugget, can be considered based on spatial characteristics. An induced compact-supported nonstationary covariance function is provided, enabling fast and memory-efficient computations when handling densely sampled domains.
Authors:
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cocons.pdf |cocons.html✨
cocons/json (API)
NEWS
# Install 'cocons' in R: |
install.packages('cocons', repos = c('https://blasif.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/blasif/cocons/issues
covariance-matrixcppestimationgaussian-processeslarge-datasetnonstationarityoptimizationprediction
Last updated 5 days agofrom:8d48bb32f8. Checks:OK: 1 WARNING: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 18 2024 |
R-4.5-win-x86_64 | WARNING | Nov 18 2024 |
R-4.5-linux-x86_64 | WARNING | Nov 18 2024 |
R-4.4-win-x86_64 | WARNING | Nov 18 2024 |
R-4.4-mac-x86_64 | WARNING | Nov 18 2024 |
R-4.4-mac-aarch64 | WARNING | Nov 18 2024 |
R-4.3-win-x86_64 | WARNING | Nov 18 2024 |
R-4.3-mac-x86_64 | WARNING | Nov 18 2024 |
R-4.3-mac-aarch64 | WARNING | Nov 18 2024 |
Exports:cocococoOptimcocoPredictcocoSimcov_rnscov_rns_classiccov_rns_predcov_rns_tapercov_rns_taper_predgetAICgetBICgetBoundariesgetBoundariesV2getBoundariesV3getCIsgetCovMatrixgetCRPSgetDensityFromDeltagetDesignMatrixgetEstimsgetHessiangetLoglikgetLogScoregetModelListsgetModHessGetNeg2loglikelihoodGetNeg2loglikelihoodProfileGetNeg2loglikelihoodREMLGetNeg2loglikelihoodTaperGetNeg2loglikelihoodTaperProfilegetScalegetSpatEffectsgetSpatMeanis.formulaplotplotOptimInfosummary
Dependencies:BHdotCall64evaluatefieldshighrknitrmapsoptimParallelRcppspamviridisLitexfunyaml