KAMP bivariate expectation (Matrix Implementation)

Computes the KAMP (K-function Adjusted for Marked Permutations) expectation for bivariate point patterns using a matrix-based approach. Note that this is slower.

See kamp_expectation_biv for the spatstat-based implementation of the KAMP bivariate expectation.

Usage

kamp_expectation_biv_mat(
  ppp_obj,
  rvals = c(0, 0.05, 0.075, 0.1, 0.15, 0.2),
  correction = "trans",
  marksvar1 = "immune1",
  marksvar2 = "immune2"
)

Arguments

ppp_obj

A point pattern object from the spatstat.geom package.

correction

Type of edge correction method. Defaults to translational.

rvec

Vector of radii at which to calculate the KAMP expectation. Defaults to c(0, 0.05, 0.075, 0.1, 0.15, 0.2).

markvar1

Variable used to mark the points in the point pattern object for the first type. Default is "immune1".

markvar2

Variable used to mark the points in the point pattern object for the second type. Default is "immune2".

Value

A dataframe with the following columns:

r

The radius at which K was calculated.

k

The observed K value

theo_csr

The theoretical K under CSR

kamp_csr

The adjusted CSR representing the KAMP permuted expectation.

kamp

The difference between observed K and KAMP CSR

Details

Bivariate KAMP Expectation (Matrix Implementation)

Examples

if (requireNamespace("spatstat.geom", quietly = TRUE) &&
    requireNamespace("spatstat.random", quietly = TRUE)) {

  # Simulates a window
  win <- spatstat.geom::owin(c(0, 1), c(0, 1))

  # Generates 200 total points
  pp <- spatstat.random::rpoispp(lambda = 200, win = win)

  # Assigns three marks: immune1, immune2, and background
  marks <- sample(c("immune1", "immune2", "background"), pp$n, replace = TRUE, prob = c(0.3, 0.3, 0.4))

  # Creates marked point pattern
  marked_pp <- spatstat.geom::ppp(pp$x, pp$y, window = win, marks = factor(marks))

  # Computes KAMP expectation
  result <- kamp_expectation_biv_mat(marked_pp, marksvar1 = "immune1", marksvar2 = "immune2")
  print(result)
}
#> Error in map(.x, .f, ...): ℹ In index: 1.
#> Caused by error in `kamp_expectation_biv_mat_helper()`:
#> ! could not find function "kamp_expectation_biv_mat_helper"