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yaImpute: An R Package for k NN Imputation
Open accessAbstract
This article introduces yaImpute, an R package for nearest neighbor search and imputation. Although nearest neighbor imputation is used in a host of disciplines, the methods implemented in the yaImpute package are tailored to imputation-based forest attribute estimation and mapping. The impetus to writing the yaImpute is a growing interest in nearest neighbor imputation methods for spatially explicit forest inventory, and a need within this research community for software that facilitates comparison among different nearest neighbor search algorithms and subsequent imputation techniques. yaImpute provides directives for defining the search space, subsequent distance calculation, and imputation rules for a given number of nearest neighbors. Further, the package offers a suite of diagnostics for comparison among results generated from different imputation analyses and a set of functions for mapping imputation results.
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Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
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Imputation with the R Package VIM
Kowarik, A., & Templ, M. (2016) · Journal of Statistical Software · doi:10.18637/jss.v074.i07 · Cited by 659
Norberg, A., Abrego, N., Blanchet, F. G., Adler, F. R., Anderson, B. J., Anttila, J., Araújo, M. B., Dallas, T., Dunson, D., Elith, J., et al. (2019) · Ecological Monographs · doi:10.1002/ecm.1370 · Cited by 573
Coops, N. C., Tompalski, P., Goodbody, T. R. H., Queinnec, M., Luther, J. E., Bolton, D. K., White, J. C., Wulder, M. A., van Lier, O. R., & Hermosilla, T. (2021) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112477 · Cited by 406
Metadata
- Authors
- Crookston, N. L., & Finley, A. O.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2008
- Volume
- 23
- Issue
- 10
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W2131472136
- Cited by
- 418
- References
- 1
- FWCI
- 12.15
- Type
- journal article
- Language
- en
- Open access
- diamond
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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