ens {divo} | R Documentation |
ens Effective Number of Species
Description
Calculates diversity profile (DP) using the effective number of species (ENS) based on inverting the Renyi entropy. For any monotone diversity index (see, Rempala and Seweryn 2013) the ENS is defined as the size of a uniform population with the same index value as the current population. The ENS may be considered as a measure of population diversity expressed in the units of species counts. The ENS profile is calculated against the Renyi entropy index, which allows for a direct comparison with the diversity profile (as in dp
). The option of performing the Horvitz-Thompson correction is available in the function ens.ht
. For more details on ENS, see Rempala and Seweryn (2013) or Jost (2006).
Usage
ens(x, alpha = seq(0.1, 2, 0.1), CI = 0.95, resample = 100,
single_graph = FALSE, pooled_graph = FALSE, csv_output = FALSE,
PlugIn = FALSE, size = 1, CVG = FALSE, saveBootstrap = FALSE)
Arguments
x |
a matrix containing input populations |
alpha |
a vector containing alpha values, default = seq(0.1, 2, 0.1) |
CVG |
a list containing alpha values multiplied by coverage; default = FALSE |
CI |
Confidence Interval default = 0.95, range (0, 1) |
resample |
set number of repetitions, default = 100 |
single_graph |
default = FALSE, plot of the Diversity Profile for each population; |
pooled_graph |
default = FALSE, plot of the Diversity Profile for all populations; |
csv_output |
save the result of the analysis as .CSV file, default = FALSE; |
PlugIn |
standard plug-in estimator, default = FALSE |
size |
resampled fraction of the population, default = 1 (actual size of populations). The value should not be smaller than 10% of population (size = 0.1) |
saveBootstrap |
Saves bootstrap result to a file. Use saveBootstrap = TRUE to save bootstrap results to a Bootstrap folder in current directory; saveBootstrap = 'FolderName' - saves bootstrap results to user-named folder |
Author(s)
Christoph Sadee, Maciej Pietrzak, Michal Seweryn, Cankun Wang, Grzegorz Rempala
Maintainer: Maciej Pietrzak pietrzak.20@osu.edu
References
Jost L. (2006) Entropy and diversity. Oikos 113:363-75
Rempala G.A., Seweryn M. Methods for diversity and overlap analysis in T-cell receptor populations. (2013) J Math Biol 67:1339-68
Examples
data(TCR.Data)
result <- ens(x, PlugIn = TRUE)