lohboot(X,
fun=c("pcf", "Kest", "pcfinhom", "Kinhom"),
..., nsim=200, confidence=0.95, global=FALSE, type=7)
"ppp"
)."pcf"
, "Kest"
, "pcfinhom"
or "Kinhom"
.FALSE
(the default), pointwise confidence intervals
are constructed. If TRUE
, a global (simultaneous) confidence band is
constructed.quantile
controlling the way the quantiles are calculated."fv"
)
containing columns giving the estimate of the summary function,
the upper and lower limits of the bootstrap confidence interval,
and the theoretical value of the summary function for a Poisson process.fun
using the bootstrap method of Loh (2008). If fun="pcf"
, for example, the algorithm computes a pointwise
(100 * confidence)
% confidence interval for the true value of
the pair correlation function pcf
for the point
process. It starts by computing the array of
local pair correlation functions,
localpcf
, of the data pattern X
.
This array consists of the contributions to pcf
from each
data point. Then these contributions are resampled nsim
times
with replacement; from each resampled dataset the total contribution
is computed, yielding nsim
random pair correlation functions.
The pointwise alpha/2
and 1 - alpha/2
quantiles of
these functions are computed, where alpha = 1 - confidence
.
To control the smoothing and estimation algorithm, use the
arguments ...
, which are passed to the local version
of the summary function, as shown below:
pcf
localpcf
Kest
localK
pcfinhom
localpcfinhom
Kinhom
localKinhom
}
An alternative to lohboot
is varblock
.
Kest
,
pcf
,
Kinhom
,
pcfinhom
,
localK
,
localpcf
,
localKinhom
,
localpcfinhom
. See varblock
for an alternative bootstrap technique.
p <- lohboot(simdat, stoyan=0.5)
plot(p)
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