Point-pattern extras: nearest neighbours, quadrats, Morisita, cross-K, segregation
Source:R/PointPatternExtra.R
KnnDistances.RdKnnDistances: distance to the k-th nearest neighbour (ties by
index), as spatstat.geom::nndist(X, k = k). QuadratTest:
Pearson \(X^2\) of \(n_x \times n_y\) equal tiles of a rectangle, with
upper-tail and two-sided p-values, as spatstat.explore::quadrat.test.
MorisitaIndex: Morisita's index, the critical indices and the
standardised index, as vegan::dispindmorisita. CrossK:
cross-type K and L with Ripley's isotropic correction, as Kcross.
SegregationTest: \(T = \sum_i \sum_m (p_m(x_i) - \bar p_m)^2\) with
leave-one-out Gaussian-kernel type probabilities and a random-relabelling
Monte Carlo p-value, as segregation.test. Identical to the Python arm
morie.fn.pppextra; indices are 1-based here.
Usage
KnnDistances(points, k = 1L)
QuadratTest(points, window, nx, ny)
MorisitaIndex(counts, crit = 0.05)
CrossK(points, marks, i, j, window, r)
SegregationTest(points, marks, sigma, nsim = 19L, seed = 1)Arguments
- points
Two-column coordinates.
- k
Neighbour order.
- window
Rectangle
c(x0, x1, y0, y1).- nx, ny
Tiles along x and y.
- counts
Quadrat counts.
- crit
Significance level of the critical indices.
- marks
Type labels.
- i, j
Types.
- r
Distances.
- sigma
Gaussian kernel bandwidth.
- nsim
Number of relabellings.
- seed
Philox seed.
References
Thompson, H. R. (1956). Distribution of distance to nth neighbour in a population of randomly distributed individuals. Ecology 37, 391-394.
Morisita, M. (1959). Measuring of the dispersion of individuals and analysis of the distributional patterns. Memoirs of the Faculty of Science, Kyushu University, Series E 2, 215-235.
Lotwick, H. W. and Silverman, B. W. (1982). Methods for analysing spatial processes of several types of points. JRSS B 44, 406-413.
Diggle, P. J., Zheng, P. and Durr, P. (2005). Nonparametric estimation of spatial segregation in a multivariate point process. Applied Statistics 54, 645-658.