ens.ht {divo} | R Documentation |
ens.ht Effective Number of Species with the Horvitz-Thompson Correction
Description
Calculates diversity profile (DP) using the effective number of species (ENS) based on inverting the Renyi entropy with the Horvitz-Thompson correction. For any monotone diversity index (see, e.g., 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 ENS without the Horvitz-Thompson correction is available as function ens
. For more details on ENS see Rempala and Seweryn (2013) or Jost (2006).
Usage
ens.ht(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.ht(x, PlugIn = TRUE)