id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_zpb5q6j2qjbcjhw5xefjwjkgse	Thomas R. Etherington	Discrete natural neighbour interpolation with uncertainty using cross-validation error-distance fields	2020	16	.pdf	application/pdf	6215	523	52	neighbour interpolation and cross-validation error-distance fields provide reliable Discrete natural neighbour interpolation with uncertainty using cross-validation errordistance fields. neighbour interpolation is the cross-validation error field (Willmott & Matsuura, 2006). that when estimated for all cells produces a cross-validation error-distance field (Fig. 3B). The discrete natural neighbour interpolation and cross-validation error-distance field (Pérez, Granger & Hunter, 2011) using the NumPy (Van der Walt, Colbert & Varoquaux, each data cell ri calculated through cross-validation, and then an estimated rate of absolute error field r̂ is To summarise the performance of both natural neighbour interpolation and the crossvalidation error-distance field, the MAE (Eq. cross-validation error-distance field (Fig. 6B) reduced as the number of data points n and (B) the resulting natural neighbour interpolation ẑ from the sampling points, and (C) value error e(ẑ) = Figure 6 Performance of natural neighbour interpolation and cross-validation error-distance fields data points, therefore as interpolations move further beyond the convex hull the error-field	./cache/work_zpb5q6j2qjbcjhw5xefjwjkgse.pdf	./txt/work_zpb5q6j2qjbcjhw5xefjwjkgse.txt