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spatstat.explore (version 3.6-0)

nnequal: Nearest Neighbour Type-Equality Function

Description

Compute the estimated nearest neighbour type-equality function for a multitype point pattern dataset.

Usage

nnequal(X, ..., kmax = 20, ratio = TRUE, cumulative = TRUE)

Value

A function value table (object of class "fv") which can be printed and plotted. The function has argument k (the order of neighbour) and columns of values labelled bord (for the border-correction estimate) and theo (for the theoretical value expected under random labelling).

Arguments

X

A multitype point pattern (object of class "ppp" with marks that are a factor).

kmax

Maximum number of neighbours to be considered for each point.

cumulative

Logical value indicating whether to compute the cumulative estimate. See Details.

ratio

Logical value indicating whether to save ratio information for future use in pooling data.

...

Ignored.

Author

Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Lucia Cobo-Sanchez.

Details

The nearest-neighbour type-equality function has two versions: cumulative and non-cumulative.

The non-cumulative version is a function \(P(k)\) which gives, for each integer \(k\), the probability that a typical point in the point pattern will have the same type as its \(k\)-th neighbour. For example \(P(5)=0.6\) would mean that there is a 60 percent chance that the fifth-nearest neighbour of a point has the same type as the original point. When cumulative=FALSE, the algorithm computes an estimate of \(P(k)\) for each integer \(k\) up to kmax, and returns the result as a function. This is equivalent to computing the nearest-neighbour correlation nncorr(X, k) for each integer k from 1 to kmax.

The cumulative version is \(Q(k) = \sum_{m=1}^k P(m)/k\). This means that \(Q(k)\) is the average proportion, amongst the nearest \(k\) neighbours of a point, which share the same type as the original point. For example \(Q(5)=0.6\) would mean that, on average, three out of the first five nearest neighbours of a point have the same type as the original point. This function is computed when cumulative=TRUE (the default).

In either case, the result is a function value table (class "fv") with two columns of values, one giving the estimate of \(P(k)\) or \(Q(k)\), and the other giving the corresponding average value for the pattern. Estimated values greater than the average suggest that points of the same type are clustered together.

References

Diez-Martin, F., Cobo-Sanchez, L., Baddeley, A., Uribelarrea, D., Mabulla, A., Baquedano, E. and Dominguez-Rodrigo, M. (2021) Tracing the spatial imprint of Oldowan technological behaviors: A view from DS (Bed I, Olduvai Gorge, Tanzania). PLOS ONE, Public Library of Science, 16, 1--47. DOI: 10.1371/journal.pone.0254603

See Also

nncount

Examples

Run this code
  plot(nnequal(lansing), ylim=c(0, 0.5))
  plot(envelope(amacrine, nnequal, nsim=19))
  plot(envelope(amacrine, nnequal, cumulative=FALSE, nsim=19))

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