For a lattice with nr rows and nc columns on only needs to compute $n=nr X nc$ entries to fill the whole covariance matrix (of size $n X n$). For example, the diagonal entries will all be the same so one only needs to compute it once and know that the value needs to be placed along the diagonal. This algorithm figures out which entries need to be computed, and how to insert them into the covariance matrix.
Observations are averages over congruent rectangular plots that like in a lattice. For extensive observations one needs to multiply the matrix by the $area^2$ where $area$ is the common area of each plot.
f
(Package: spatialCovariance) :
Density For Distance Between Two Points In Rectangles
This evaluates the density for the distance between two points, each distribution uniformly and independently in rectangles. The rectangles are congruent and lie on a lattice. Three special cases exist, when the two rectangles coincide, when the two rectangles lie on the same row (or column) of the lattice and when the two rectangles lie on different rows and columns.
● Data Source:
CranContrib
● Keywords: spatial
● Alias: f
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