Computes quadrature weights for a given set of points, using the ``counting weights'' for a grid of rectangular tiles.
gridweights(X, ntile, …, window=NULL, verbose=FALSE, npix=NULL, areas=NULL)Data defining a point pattern.
Number of tiles in each row and column of the rectangular grid. An integer vector of length 1 or 2.
Ignored.
Default window for the point pattern
Logical flag. If TRUE, information will be printed
about the computation of the grid weights.
Dimensions of pixel grid to use when computing a digital approximation to the tile areas.
Vector of areas of the tiles, if they are already known.
Vector of nonnegative weights for each point in X.
This function computes a set of quadrature weights
for a given pattern of points
(typically comprising both ``data'' and `dummy'' points).
See quad.object for an explanation of quadrature
weights and quadrature schemes.
The weights are computed by the ``counting weights'' rule
based on a regular grid of rectangular tiles.
First X and (optionally) window are converted into a
point pattern object. Then the bounding rectangle of the window of
the point pattern is
divided into a regular ntile[1] * ntile[2] grid of rectangular tiles.
The weight attached to a point of X is the area of the tile
in which it lies, divided by the number of points of X lying in
that tile.
For non-rectangular windows the tile areas are currently calculated
by approximating the window as a binary mask. The accuracy of this
approximation is controlled by npix, which becomes
the argument dimyx of as.mask.
# NOT RUN {
Q <- quadscheme(runifpoispp(10))
X <- as.ppp(Q) # data and dummy points together
w <- gridweights(X, 10)
w <- gridweights(X, c(10, 10))
# }