localSTLKinhom {stopp}

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
)

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.

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.

Value

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

Author(s)

Nicoletta D'Angelo

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)