bayesian - Bindings for Bayesian TidyModels
Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels' via 'bayesian' <doi:10.5281/zenodo.4426836>. 'tidymodels' is a collection of packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) <doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>, and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
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bayesianbrmsstantidymodels
7.76 score 48 stars 46 scripts 746 downloadsHiClimR - Hierarchical Climate Regionalization
A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution, geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function with preliminary big data support, different clustering methods, hybrid hierarchical clustering, multivariate clustering (MVC), cluster validation, visualization of regionalization results, and exporting region map and mean timeseries into NetCDF-4 file. The technical details are described in Badr et al. (2015) <doi:10.1007/s12145-015-0221-7>.
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clusteringcontiguityhomogeneitymultivariateregionalizationspatiotemporal
7.74 score 16 stars 3 dependents 73 scripts 1.3k downloadsadditive - Bindings for Additive TidyModels
Fit Generalized Additive Models (GAM) using 'mgcv' with 'parsnip'/'tidymodels' via 'additive' <doi:10.5281/zenodo.4784245>. 'tidymodels' is a collection of packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>). The technical details of 'mgcv' are described in Wood (2017) <doi:10.1201/9781315370279>.
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additivebamgamgeneralized-additive-modelsmgcvtidymodels
6.16 score 8 stars 15 scripts 695 downloads