kdayday/forecasting: Probabilistic Solar Forecsting
Generate and evaluate probabilistic solar forecasts, focusing on post-processing numerical weather prediction ensembles. Options include empirical cumulative distribution functions (CDFs) suitable for raw ensembles and persistence ensembles; Bayesian model averaging (BMA) and ensemble model output statistics (EMOS) post-processing, and some discontinued attempts at kernel density estimation and spatial aggregation with copulas (not exported).
Getting started
Browse package contents
Package details |
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| Author | person("Kate", "Doubleday", email = "kate.doubleday@nrel.gov", role = c("aut", "cre")) |
| Maintainer | Kate Doubleday <kate.doubleday@nrel.gov> |
| License | MIT + file LICENSE |
| Version | 1.0.0 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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