View source: R/alpha_div_test.R
hill_test_rarperm_pq | R Documentation |
This reduce the risk of a random drawing of a exceptional situation of an unique rarefaction.
hill_test_rarperm_pq(
physeq,
fact,
hill_scales = c(0, 1, 2),
nperm = 99,
sample.size = min(sample_sums(physeq)),
verbose = FALSE,
progress_bar = TRUE,
p_val_signif = 0.05,
type = "non-parametrique",
...
)
physeq |
(required): a |
fact |
(required) Name of the factor in |
hill_scales |
(a vector of integer) The list of q values to compute the hill number H^q. If Null, no hill number are computed. Default value compute the Hill number 0 (Species richness), the Hill number 1 (exponential of Shannon Index) and the Hill number 2 (inverse of Simpson Index). |
nperm |
(int) The number of permutations to perform. |
sample.size |
(int) A single integer value equal to the number of
reads being simulated, also known as the depth. See
|
verbose |
(logical). If TRUE, print additional informations. |
progress_bar |
(logical, default TRUE) Do we print progress during the calculation? |
p_val_signif |
(float, |
type |
A character specifying the type of statistical approach
(See
|
... |
Other arguments passed on to |
A list of 6 components :
method
expressions
plots
pvals
prop_signif
statistics
Adrien Taudière
ggstatsplot::ggbetweenstats()
, hill_pq()
if (requireNamespace("ggstatsplot")) {
hill_test_rarperm_pq(data_fungi, "Time", nperm = 2)
res <- hill_test_rarperm_pq(data_fungi, "Height", nperm = 9, p.val = 0.9)
patchwork::wrap_plots(res$plots[[1]])
res$plots[[1]][[1]] + res$plots[[2]][[1]] + res$plots[[3]][[1]]
res$prop_signif
res_para <- hill_test_rarperm_pq(data_fungi, "Height", nperm = 9, type = "parametrique")
res_para$plots[[1]][[1]] + res_para$plots[[2]][[1]] + res_para$plots[[3]][[1]]
res_para$pvals
res_para$method
res_para$expressions[[1]]
}
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