Compute an estimate of the space-time K LISTA functions.
KLISTAhat(xyt, s.region, t.region, dist, times, lambda, correction = "isotropic")A list containing:
A list containing the values of the estimation of \(K^{(i)}(r,t)\) for each one of \(n\) points of the point pattern by matrixs.
ndist x ntimes matrix containing theoretical values for a Poisson process.
Parameters passed in argument.
The name(s) of the edge correction method(s) passed in argument.
Coordinates and times \((x,y,t)\) of the point pattern.
Two-column matrix specifying polygonal region containing all data locations. If s.region is missing, the bounding box of xyt[,1:2] is considered.
Vector containing the minimum and maximum values of the time interval. If t.region is missing, the range of xyt[,3] is considered.
Vector of distances \(u\) at which \(K^{(i)}(u,v)\) is computed. If missing, the maximum of dist is given by \(\min(S_x,S_y)/4\), where \(S_x\) and \(S_y\) represent the maximum width and height of the bounding box of s.region.
Vector of times \(v\) at which \(K^{(i)}(u,v)\) is computed. If missing, the maximum of times is given by \((T_{\max} - T_{\min})/4\), where \(T_{\min}\) and \(T_{\max}\) are the minimum and maximum of the time interval \(T\).
Vector of values of the space-time intensity function evaluated at the points \((x,y,t)\) in \(S\times T\). If lambda is missing, the estimate of the space-time pair correlation function is computed as for the homogeneous case, i.e. considering \((n-1)/|S \times T|\) as an estimate of the space-time intensity.
A character vector specifying the edge correction(s) to be applied among "isotropic", "border", "modified.border", "translate" and "none" (see PCFhat). The default is "isotropic".
Francisco J. Rodriguez-Cortes <frrodriguezc@unal.edu.co>
An individual product density LISTA functions \(K^{(i)}(.,.)\) should reveal the extent of the contribution of the event \((u_i,t_i)\) to the global estimator of the K-function \(K(.,.)\), and may provide a further description of structure in the data (e.g., determining events with similar local structure through dissimilarity measures of the individual LISTA functions), for more details see Siino et al. (2019).
Baddeley, A. and Turner, J. (2005). spatstat: An R Package for Analyzing Spatial Point Pattens. Journal of Statistical Software 12, 1-42.
Cressie, N. and Collins, L. B. (2001). Analysis of spatial point patterns using bundles of product density LISA functions. Journal of Agricultural, Biological, and Environmental Statistics 6, 118-135.
Cressie, N. and Collins, L. B. (2001). Patterns in spatial point locations: Local indicators of spatial association in a minefield with clutter Naval Research Logistics (NRL), John Wiley & Sons, Inc. 48, 333-347.
Siino, M., Adelfio, G., Mateu, J. and Rodriguez-Cortes, F. J. (2019). Some properties of weighted local second-order statistcs for spatio-temporal point process. Submitted.
Stoyan, D. and Stoyan, H. (1994). Fractals, random shapes, and point fields: methods of geometrical statistics. Chichester: Wiley.