ataKriging {atakrig} | R Documentation |
Area-to-area, area-to-point ordinary Kriging prediciton, cross-validation.
Description
Area-to-area, area-to-point ordinary Kriging prediciton, cross-validation.
Usage
ataKriging(x, unknown, ptVgm, nmax = 10, longlat = FALSE,
showProgress = FALSE, nopar = FALSE, clarkAntiLog = FALSE)
atpKriging(x, unknown0, ptVgm, nmax = 10, longlat=FALSE,
showProgress = FALSE, nopar = FALSE)
ataKriging.cv(x, nfold = 10, ptVgm, nmax=10, longlat = FALSE,
showProgress = FALSE, nopar = FALSE, clarkAntiLog = FALSE)
Arguments
x |
a discreteArea object: list(areaValues, discretePoints), where areaValues: data.frame(areaId,centx,centy,value) discretePoints: data.frame(areaId,ptx,pty,weight) |
unknown |
a discreted discreteArea object, or just data.frame(areaId,ptx,pty,weight). |
unknown0 |
for points prediction, data.frame(ptx,pty), one point per row. |
nfold |
number of fold for cross-validation. for leave-one-out cross-validation, nfold = nrow(x$areaValues). |
ptVgm |
point scale variogram, ataKrigVgm. |
nmax |
max number of neighborhoods used for interpolation. |
longlat |
coordinates are longitude/latitude or not. |
showProgress |
show progress bar for batch interpolation (multi destination areas). |
nopar |
disable parallel process in the function even if ataStartCluster() has been called, mainly for internal use. |
clarkAntiLog |
for log-transformed input data, whether the estimated value should be adjusted(i.e. exponentiation). |
Value
estimated value of destination area and its variance.
References
Clark, I., 1998. Geostatistical estimation and the lognormal distribution. Geocongress. Pretoria, RSA., [online] Available from: http://kriging.com/publications/Geocongress1998.pdf. Goovaerts, P., 2008. Kriging and semivariogram deconvolution in the presence of irregular geographical units. Mathematical Geosciences 40 (1): 101-128. Isaaks, E. H., Srivastava, R. M., 1989. An introduction to applied geostatistics. New York, Oxford University Press. Skøien, J. O. and G. Blöschl, et al., 2014. rtop: an R package for interpolation of data with a variable spatial support, with an example from river networks. Computers & Geosciences 67: 180-190.
See Also
Examples
library(atakrig)
library(sf)
## load demo data from rtop package ----
if (!require("rtop", quietly = TRUE)) message("rtop library is required for demo data.")
rpath <- system.file("extdata", package="rtop")
observations <- read_sf(rpath, "observations")
observations$obs <- observations$QSUMMER_OB/observations$AREASQKM
## point-scale variogram ----
obs.discrete <- discretizePolygon(observations, cellsize=1500, id="ID", value="obs")
pointsv <- deconvPointVgm(obs.discrete, model="Exp", ngroup=12, rd=0.75, fig=TRUE)
## cross validation ----
pred.cv <- ataKriging.cv(obs.discrete, nfold=length(observations), pointsv)
names(pred.cv)[6] <- "obs"
summary(pred.cv[,c("obs","pred","var")])
cor(pred.cv$obs, pred.cv$pred) # Pearson correlation
mean(abs(pred.cv$obs - pred.cv$pred)) # MAE
sqrt(mean((pred.cv$obs - pred.cv$pred)^2)) # RMSE
## prediction ----
predictionLocations <- read_sf(rpath, "predictionLocations")
pred.discrete <- discretizePolygon(predictionLocations, cellsize = 1500, id = "ID")
pred <- ataKriging(obs.discrete, pred.discrete, pointsv$pointVariogram)