stopp (version 0.2.3)

localSTLKinhom: Local inhomogeneous Spatio-temporal K-functions on a linear network

Description

The functions localSTLKinhom and localSTLginhom implement the inhomogeneous LISTA functions proposed in D'Angelo et al. (2022).

Usage

localSTLKinhom(
  x,
  lambda = lambda,
  normalize = FALSE,
  r = NULL,
  t = NULL,
  nxy = 10
)

Value

A list of class lista. The objects are of class sumstlpp (Moradi and Mateu, 2020).

Arguments

x

A realisation of a spatio-temporal point processes on a linear network in stlp format

lambda

values of estimated intensity.

normalize

normalization factor to be considered.

r

values of argument r where K-function will be evaluated. optional.

t

values of argument t where K-function will be evaluated. optional.

nxy

pixel array dimensions. optional.

Author

Nicoletta D'Angelo

Details

The homogeneous K-function and pair correlation functions, in D'Angelo et al. (2021), can be obtained easily with localSTLKinhom and localSTLginhom, by imputing a lambda vector of constant intensity values, the same for each point.

References

D’Angelo, N., Adelfio, G., and Mateu, J. (2021). Assessing local differences between the spatio-temporal second-order structure of two point patterns occurring on the same linear network. Spatial Statistics, 45, 100534.

D’Angelo, N., Adelfio, G., and Mateu, J. (2022). Local inhomogeneous second-order characteristics for spatio-temporal point processes on linear networks. Stat Papers. https://doi.org/10.1007/s00362-022-01338-4

See Also

localSTLginhom, STLKinhom, STLginhom

Examples

set.seed(2)
df_net <- data.frame(x = runif(25, 0, 0.85), y = runif(25, 0, 0.85), t = runif(25))
stlp1 <- stp(df_net, L = chicagonet)
lambda <- rep(diff(range(stlp1$df$x)) * diff(range(stlp1$df$y))
 * diff(range(stlp1$df$t)) / spatstat.geom::volume(stlp1$L),
nrow(stlp1$df))

k <- localSTLKinhom(stlp1, lambda = lambda, normalize = TRUE)