## S3 method for class 'msr':
with(data, expr, \dots)
"msr"
).with
for the class "msr"
.
The argument data
should be an object of class "msr"
representing a measure (a function which assigns a value to each
subset of two-dimensional space).This function can be used to extract the components of the measure, or to perform more complicated manipulations of the components.
The argument expr
should be an un-evaluated expression
in the Rlanguage. The expression may involve any of the variable
names listed below with their corresponding meanings.
qlocations
(point pattern) all quadrature locations
qweights
(numeric) all quadrature weights
density
(numeric) density value at each quadrature point
discrete
(numeric) discrete mass at each quadrature point
continuous
(numeric) increment of continuous component
increment
(numeric) increment of measure
is.atom
(logical) whether quadrature point is an atom
atoms
(point pattern) locations of atoms
atommass
(numeric) massess of atoms
}
The measure is the sum of discrete and continuous components.
The discrete component assigns non-zero mass to several points called atoms.
The continuous component has a density which should be integrated
over a region to determine the value for that region.
An object of class "msr"
approximates the continuous component
by a sum over quadrature points. The quadrature points are chosen
so that they include the atoms of the measure. In the list above,
we have increment = continuous + discrete
,
continuous = density * qweights
,
is.atom = (discrete > 0)
,
atoms = qlocations[is.atom]
and
atommass = discrete[is.atom]
.
msr
X <- rpoispp(function(x,y) { exp(3+3*x) })
fit <- ppm(X, ~x+y)
rp <- residuals(fit, type="pearson")
with(rp, atoms)
with(rp, qlocations %mark% continuous)
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