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)`

X

Data defining a point pattern.

ntile

Number of tiles in each row and column of the rectangular grid. An integer vector of length 1 or 2.

…

Ignored.

window

Default window for the point pattern

verbose

Logical flag. If `TRUE`

, information will be printed
about the computation of the grid weights.

npix

Dimensions of pixel grid to use when computing a digital approximation to the tile areas.

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(runifrect(15)) X <- as.ppp(Q) # data and dummy points together w <- gridweights(X, 10) w <- gridweights(X, c(10, 10)) # }