TODO.

pm_analysis(
  proj,
  n_perms = 1000,
  n_breaks = 50,
  min_dist = 0,
  max_dist = Inf,
  min_group_size = 5,
  check_internal = FALSE,
  report_progress = TRUE,
  pb_markdown = FALSE
)

Arguments

proj

object of class pm_project.

n_perms

number of permutations in test.

n_breaks

values are broken into this many groups based on spatial distances. Permutation testing then occurs within groups. Hence, a larger value of n_breaks does a better job of conditioning on spatial distance, but comes at the cost of statistical power in permutation testing. A warning is printed if any group ends up containing fewer than 10 edges.

min_dist, max_dist

minimum and maximum edge lengths to be included in the analysis. Anything outside this range is ignored.

min_group_size

minimum number of edges within a spatial permutation group, otherwise edges within this group are replaced with NA.

check_internal

if TRUE then spatial distance is used as statistical distance in place of the loaded matrix. This option acts as an internal check, because statistical significance should not be seen when spatial distance is tested against itself. If you do see areas of significance then it is likely you are not using enough n_breaks to account for the trend with distance in the data.

report_progress

if TRUE then a progress bar is printed to the console during the permutation testing procedure.

pb_markdown

whether to run progress bars in markdown mode, in which case they are updated once at the end to avoid large amounts of output.