unbiasedKrige {intamap} | R Documentation |
unbiasedKrige
is a function for modifying a kriging prediction
to a prediction that can be assumed to be unbiased for a certain threshold.
unbiasedKrige(object, formulaString, observations, predictionLocations, model, outputWhat, nmax, nsim, yamamoto, debug.level, ...)
object |
either an object of the intamap type (see intamap-package
for further
description of the necessary content of this variable) or the output from the function
krige in gstat . If the object is a result
from the intamap procedure spatialPredict, the remaining arguments are not necessary. |
formulaString |
formula that defines the dependent variable as a linear model of independent variables; suppose the dependent variable has name z, for ordinary and simple kriging use the formula z~1; for universal kriging, suppose z is linearly dependent on x and y, use the formula z~x+y |
observations |
a Spatial *DataFrame with observations;
should contain the dependent variable, independent variables, and coordinates |
predictionLocations |
the predictionLocations, only necessary if the method is "IWQSEL" and formulaString contains independent variables. Should preferentally be a grid if the method is "IWQSEL" |
model |
variogram model of dependent variable (or its residuals), defined
by a call to vgm or autofitVariogram |
outputWhat |
Argument with type of unbiasedness method ("MOK" or "IWQSEL") and the thresholds. |
nmax |
for local kriging: the number of nearest observations that should be used in simulations for the "IWQSEL" method in terms of the space of the spatial locations. Defaults to nmax = 10 when object is a Spatial*DataFrame. |
nsim |
number of simulations necessary if the method is "IWQSEL".
Defaults to nsim = 100 when object is a Spatial *DataFrame. |
yamamoto |
logical describing if the yamamoto approach )is to be used in simulations.
Defaults to yamamoto = FALSE when object is a Spatial *DataFrame. |
debug.level |
debug level, passed to subfunctions |
... |
other arguments that will be passed to subfunctions |
It is a fact that predictions from kriging tend to be biased towards the mean of
the process. The function unbiasedKrige
is a function that adds one or more predictions
to the original output, which are assumed to be unbiased relative to a certain
threshold. The two methods supported are the IWQSEL-method (Craigmile, 2006) and
MOK (Skoien et al, 2008).
an object of type intamap, as described in intamap-package
, or a
Spatial
*DataFrame with one or more new prediction columns, representing different
methods and thresholds.
Jon Olav Skoien
Craigmile, P. F., N. Cressie, T. J. Santner, and Y. Rao. 2006. A loss function approach to identifying environmental exceedances. Extremes, 8, 143-159.
Skoien, J. O., G. B. M. Heuvelink, and E. J. Pebesma. 2008. Unbiased block predictions and exceedance probabilities for environmental thresholds. In: J. Ortiz C. and X. Emery (eds). Proceedings of the eight international geostatistics congress. Gecamin, Santiago, Chile, pp. 831-840.
library(intamap) data(meuse) data(meuse.grid) coordinates(meuse) = ~x+y gridded(meuse.grid) = ~x+y predictionLocations = coarsenGrid(meuse.grid,5,) vmod = autofitVariogram(log(zinc)~1,meuse)$var_model prediction = krige(log(zinc)~1,meuse,predictionLocations,vmod) summary(prediction) prediction = unbiasedKrige(prediction,log(zinc)~1, meuse, model = vmod, outputWhat = list(MOK = 6.0, MOK = 7.0, IWQSEL=7.0)) summary(prediction)