Closed Aariq closed 1 month ago
Going to bump this to the next sprint in hopes that someone will share example code for the NCV paper (https://github.com/cct-datascience/organization/issues/2091).
https://fosstodon.org/deck/@millerdl@mathstodon.xyz/112498626465593674
So not sure what the "neighborhoods" are when NCV is applied to a raster dataset. Is it some area around every pixel? If so, that feels impractical. Going to do some reading about spatial CV:
Brenning, A., 2012. Spatial cross-validation and bootstrap for the assessment of prediction rules in remote sensing: The R package sperrorest, in: 2012 IEEE International Geoscience and Remote Sensing Symposium. Presented at the 2012 IEEE International Geoscience and Remote Sensing Symposium, pp. 5372–5375. https://doi.org/10.1109/IGARSS.2012.6352393
Le Rest, K., Pinaud, D., Monestiez, P., Chadoeuf, J., Bretagnolle, V., 2014. Spatial leave-one-out cross-validation for variable selection in the presence of spatial autocorrelation. Global Ecology and Biogeography 23, 811–820. https://doi.org/10.1111/geb.12161
Going to close this for now as it has become more of a quest to get NCV working. Follow up in #30 includes "choose correct number of knots"
Talked with @diazrenata and came up with the following ideas for getting the number of knots right:
?choose.k
and do the thing where you look for patterns in the residualsk
don't produce qualitative statistical changes, they probably don't matter muchk
more in the interaction term than in the main effects (maybe should ask someone if this is a legit thing to do though)Originally posted by @Aariq in https://github.com/usa-npn/cales-thermal-calendars/issues/23#issuecomment-2110745185