Hi All, Just thought you might be interested in a recently released R package, spm: Spatial Predictive Modelling.
It aims to introduce some novel, accurate, hybrid geostatistical and machine learning methods for spatial predictive modelling. Of 22 functions available in spm, two functions are for accuracy assessment. Perhaps they are not only useful tools for spatial predictive modelling work, but also for other predictive modelling work in general. For the reasons of the predictive accuracy measures used in these two functions, please see: Li, J., 2016. Assessing spatial predictive models in the environmental sciences: accuracy measures, data variation and variance explained. Environmental Modelling & Software 80 1-8. http://www.sciencedirect.com/science/article/pii/S136481521630024X. Li, J., 2017. Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what? PLOS ONE 12 (8): e0183250. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0183250. The package, spm, can be downloaded from CRAN now. Any feedback and comments are much appreciated! Kind regards, Jin Jin Li, PhD | Spatial Modeller / Computational Statistician National Earth and Marine Observations | Environmental Geoscience Division t: +61 2 6249 9899 www.ga.gov.au Geoscience Australia Disclaimer: This e-mail (and files transmitted with it) is intended only for the person or entity to which it is addressed. If you are not the intended recipient, then you have received this e-mail by mistake and any use, dissemination, forwarding, printing or copying of this e-mail and its file attachments is prohibited. The security of emails transmitted cannot be guaranteed; by forwarding or replying to this email, you acknowledge and accept these risks. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
