hypervolume (version 3.0.3)

hypervolume_n_occupancy_test: Significance of random points occupancy

Description

Calculates overlap for two hypervolumes.

Usage

hypervolume_n_occupancy_test(observed,
  path,
  alternative = "two_sided",
  CI = 0.95,
  cores = 1)

Arguments

observed

An HypervolumeList generated from hypervolume_n_occupancy.

path

A path to a directory of permuted hypervolumes generated with hypervolume_n_occupancy_permute.

alternative

Alternative hypothesis, can be one of two_sided, more, less or more_less.

CI

Desired confidence interval proportion.

cores

Number of logical cores to use while generating permuted hypervolumes. If parallel backend already registered to doParallel, function will use that backend and ignore the argument in cores.

Value

An HypervolumeList with length equal to the number of pairwise combination of the observed HypervolumeList elements. ValueAtRandomPoints are calculated as the difference between the ValueAtRandomPoints of the first and the second group for each pairwise combinations. Only significant values are retained according to CI.

Details

The observed difference between ValueAtRandomPoints of two groups is compared against null expectations generated with hypervolume_n_occupancy_permute.

Examples

# NOT RUN {
data(penguins,package='palmerpenguins')
penguins_no_na = as.data.frame(na.omit(penguins))


penguins_no_na_split = split(penguins_no_na, 
              paste(penguins_no_na$species, penguins_no_na$sex, sep = "_"))


hv_list = lapply(penguins_no_na_split, function(x) 
      hypervolume_gaussian(x[, c("bill_length_mm","bill_depth_mm","flipper_length_mm")],
      samples.per.point=100))

names(hv_list) <- names(penguins_no_na_split)
hv_list <- hypervolume_join(hv_list)


hv_occupancy_list_sex <- hypervolume_n_occupancy(hv_list, 
                          classification = rep(c("female", "male"), each = 3))

# takes 99 permutations on 1 core
hyper_permuted <- hypervolume_n_occupancy_permute("permute", 
          hv_occupancy_list_sex, hv_list, classification = rep(c("female", "male"), each = 3), 
          n = 99, cores = 1)

hypervolume_test <- hypervolume_n_occupancy_test(hv_occupancy_list_sex, hyper_permuted, 
                      alternative = "more")


# }