Resample a Point Pattern by Resampling Quadrats
Given a point pattern dataset, create a resampled point pattern by dividing the window into rectangular quadrats and randomly resampling the list of quadrats.
quadratresample(X, nx, ny=nx, ..., replace = FALSE, nsamples = 1, verbose = (nsamples > 1))
- A point pattern dataset (object of class
- Numbers of quadrats in the $x$ and $y$ directions.
- Logical value. Specifies whether quadrats should be sampled with or without replacement.
- Number of randomised point patterns to be generated.
- Logical value indicating whether to print progress reports.
This command implements a very simple bootstrap resampling procedure
for spatial point patterns
X must be a point pattern (object of class
"ppp") and its observation window must be a rectangle.
The window is first divided into
N = nx * ny rectangular tiles
(quadrats) of equal size and shape.
To generate one resampled point pattern, a random sample of
N quadrats is selected from the list of
with replacement (if
replace=TRUE) or without replacement
replace=FALSE). The $i$th quadrat in the original
dataset is then replaced by the $i$th sampled quadrat, after the
latter is shifted so that it
occupies the correct spatial position. The quadrats are then
reconstituted into a point pattern inside the same window as
replace=FALSE, this procedure effectively involves a random
permutation of the quadrats. The resulting resampled point pattern has
the same number of points as
replace=TRUE, the number of points in the resampled point
pattern is random.
- A point pattern (if
nsamples = 1) or a list of point patterns (if
nsamples > 1).
varblock to estimate the variance of
a summary statistic by block resampling.
data(bei) quadratresample(bei, 6, 3)