waywiser: Ergonomic Methods for Assessing Spatial Models
Assessing predictive models of spatial data can be challenging, both because these models are typically built for extrapolating outside the original region represented by training data and due to potential spatially structured errors, with "hot spots" of higher than expected error clustered geographically due to spatial structure in the underlying data. Methods are provided for assessing models fit to spatial data, including approaches for measuring the spatial structure of model errors, assessing model predictions at multiple spatial scales, and evaluating where predictions can be made safely. Methods are particularly useful for models fit using the 'tidymodels' framework. Methods include Moran's I ('Moran' (1950) <doi:10.2307/2332142>), Geary's C ('Geary' (1954) <doi:10.2307/2986645>), Getis-Ord's G ('Ord' and 'Getis' (1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>), agreement coefficients from 'Ji' and Gallo (2006) (<doi:10.14358/PERS.72.7.823>), agreement metrics from 'Willmott' (1981) (<doi:10.1080/02723646.1981.10642213>) and 'Willmott' 'et' 'al'. (2012) (<doi:10.1002/joc.2419>), an implementation of the area of applicability methodology from 'Meyer' and 'Pebesma' (2021) (<doi:10.1111/2041-210X.13650>), and an implementation of multi-scale assessment as described in 'Riemann' 'et' 'al'. (2010) (<doi:10.1016/j.rse.2010.05.010>).
| Version: | 0.6.0 |
| Depends: | R (≥ 4.0) |
| Imports: | dplyr (≥ 1.1.0), fields, FNN, glue, hardhat, Matrix, purrr, rlang (≥ 1.1.0), sf (≥ 1.0-0), spdep (≥ 1.1-9), stats, tibble, tidyselect, vctrs, yardstick (≥ 1.2.0) |
| Suggests: | applicable, caret, CAST, covr, exactextractr, ggplot2, knitr, modeldata, recipes, rmarkdown, rsample, spatialsample, terra, testthat (≥ 3.0.0), tidymodels, tidyr, tigris, units, vip, whisker, withr |
| Published: | 2024-06-27 |
| DOI: | 10.32614/CRAN.package.waywiser |
| Author: | Michael Mahoney 
[aut, cre],
Lucas Johnson
[ctb],
Virgilio Gómez-Rubio [rev] (Virgilio reviewed the package (v.
0.2.0.9000) for rOpenSci, see
<https://github.com/ropensci/software-review/issues/571>),
Jakub Nowosad [rev] (Jakub reviewed the package (v. 0.2.0.9000) for
rOpenSci, see
<https://github.com/ropensci/software-review/issues/571>),
Posit Software, PBC [cph, fnd] |
| Maintainer: | Michael Mahoney <mike.mahoney.218 at gmail.com> |
| BugReports: | https://github.com/ropensci/waywiser/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/ropensci/waywiser, https://docs.ropensci.org/waywiser/ |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | waywiser citation info |
| Materials: | README NEWS |
| In views: | Spatial |
| CRAN checks: | waywiser results |
Documentation:
| Reference manual: | waywiser.pdf |
| Vignettes: |
Multi-scale model assessment Calculating residual spatial autocorrelation Assessing Models with waywiser |
Downloads:
| Package source: | waywiser_0.6.0.tar.gz |
| Windows binaries: | r-devel: waywiser_0.6.0.zip, r-release: waywiser_0.6.0.zip, r-oldrel: waywiser_0.6.0.zip |
| macOS binaries: | r-release (arm64): waywiser_0.6.0.tgz, r-oldrel (arm64): waywiser_0.6.0.tgz, r-release (x86_64): waywiser_0.6.0.tgz, r-oldrel (x86_64): waywiser_0.6.0.tgz |
| Old sources: | waywiser archive |
Linking:
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