pm_analysis: Perform PlasmoMAPI analysis
In mrc-ide/PlasmoMAPI: Mapping Plasmodium Spatial Connectivity from Genetic Data

Runs the main PlasmoMAPI analysis. Statistical distances are binned by edge lengths and normalised within each bin. Then raw scores are calculated for eac hex and compared against their sampling distribution, obtained via permutation testing, to arrive at z-scores. A range-limited version of this analysis can be specified by setting the minimum and maximum allowed distances.

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
)

`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.