spatstat.core (version 2.1-2)

quadratresample: Resample a Point Pattern by Resampling Quadrats

Description

Given a point pattern dataset, create a resampled point pattern by dividing the window into rectangular quadrats and randomly resampling the list of quadrats.

Usage

quadratresample(X, nx, ny=nx, ...,
                replace = FALSE, nsamples = 1,
                verbose = (nsamples > 1))

Arguments

X

A point pattern dataset (object of class "ppp").

nx,ny

Numbers of quadrats in the \(x\) and \(y\) directions.

Ignored.

replace

Logical value. Specifies whether quadrats should be sampled with or without replacement.

nsamples

Number of randomised point patterns to be generated.

verbose

Logical value indicating whether to print progress reports.

Value

A point pattern (if nsamples = 1) or a list of point patterns (if nsamples > 1).

Details

This command implements a very simple bootstrap resampling procedure for spatial point patterns X.

The dataset 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 N quadrats, with replacement (if replace=TRUE) or without replacement (if 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 X.

If replace=FALSE, this procedure effectively involves a random permutation of the quadrats. The resulting resampled point pattern has the same number of points as X. If replace=TRUE, the number of points in the resampled point pattern is random.

See Also

quadrats, quadratcount.

See varblock to estimate the variance of a summary statistic by block resampling.

Examples

# NOT RUN {
  data(bei)
  quadratresample(bei, 6, 3)
# }