The function tries to identify differences between different networks of observation stations that share a region. From these differences, biases are estimated, and can be removed.
findLocalBias(object, gid = "group",
formulaString = value ~ 1, regCode="regCode",...)
removeLocalBias(object, localBias, gid = "group", formulaString = value ~ 1,
regCode = "regCode")
From findLocalBias
: A list consisting of one element for each regional
network, or an element single
if only one regional network is apparent. Each of these elements is again a list
consisting of several other elements, where bias
is the interesting one.
The remaining elements are only necessary for debugging purposes. The elements
D, V and Q refers to the matrices with same names in Skoien et al. (2009), i.e.
the relationship matrix, the variance matrix and the difference matrix.
From removeLocalBias
: A SpatialPointsDataFrame
with the biases subtracted.
data frame with observations
name of column identifying groups of local networks
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
the column name of regions in the object
, if existing
List of data frames, for a single region, or for
each of the regions, each containing
biases for different networks in the region(s), result of
findLocalBias
arguments to be passed to sub-functions
Jon Olav Skoien
findLocalBias
tries to identify biases between overlapping networks, i.e. when
there is no boundary between different networks sampling the same type of data.
This can typically happen if different governmental bodies are responsible for
different types of measurement, e.g. one measuring the situation around populated
areas, the other one measuring close to water bodies.
The function will then try to find the difference between the different networks, and estimate the individual bias for each network, relative to a reference value, usually the average of all networks. The method is not recommended if there can be assumed to be a dependency beteween the process and the networks.
removeLocalBias
removes the bias estimated in findLocalBias
.
Skoien, J. O., O. P. Baume, E. J. Pebesma, and G. B. M. Heuvelink. 2010. Identifying and removing heterogeneities between monitoring networks. Environmetrics 21(1), 66-84.
# Assuming that the soil type is the source of biases
data(meuse)
coordinates(meuse) = ~x+y
lb = findLocalBias(meuse,gid = "soil",formulaString=as.formula(zinc~1))
lb$single$bias
meuseUnbias = removeLocalBias(meuse,localBias = lb, gid = "soil",
formulaString = zinc~1)
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