pg.ht {divo}

pg.ht Power-Geometric Index with the Horvitz-Thompson Correction

Description

The Horvitz-Thompson corrected version of the Power Geometric (PG) index (see help for pg). The PG index is a generalization of the Morisita-Horn index as well as the Bhattacharyya's coefficient. It quantifies overlap as cosine of an angle between two exponentially normalized population vectors. For further details and definitions, see Rempala and Seweryn (2013).

Usage

pg.ht(x, alpha = 1, beta=alpha, CI = 0.95, resample = 100, graph = FALSE, 
csv_output = FALSE, PlugIn = FALSE, size = 1, CVG = FALSE, saveBootstrap = FALSE)

Arguments

x

a matrix containing input populations

alpha

PG of order alpha < 1 puts more weight on the rare species and the I Index of order alpha > 1 puts more weight on the abundant ones for first population, default = 1

beta

PG of order beta < 1 puts more weight on the rare species and the I Index of order beta > 1 puts more weight on the abundant ones for second population, default = alpha

CVG

PG of order alpha or beta = coverage. If CVG = TRUE argument alpha is ignored; default = FALSE

CI

Confidence Interval default = 0.95, range (0, 1)

resample

set number of repetitions, default = 100

graph

default = FALSE, plot the results of hierarchical clustering of pairwise analysis of Power-Geometric Index, graph = 'fileName' user-defined output file name

csv_output

save the result of the analysis as .CSV file, default = FALSE; csv_output = 'fileName' user-defined output file name

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 [e-mail]

References

Rempala G.A., Seweryn M. (2013) Methods for diversity and overlap analysis in T-cell receptor populations. J Math Biol 67:1339-68

Examples

data(TCR.Data)
result <- pg.ht(x, PlugIn = TRUE)