i.inp Information Index (I index) for 2-Way, 2 Column Table

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Description

The I-index is a measure of overlap in two way tables based on the generalized mutual information statistic. This function implements a special case of table with two columns only. In general, the I-index measures dependence in any two-way tables, taking values between 0 and 1. It returns a value of zero when the table columns form an orthogonal system and a value of one when the table columns rank is one. The value of the parameter alpha is related to the structure of dependence, as described in Rempala and Seweryn (2013).

Usage

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i.inp(x, alpha = 1, 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

I index 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, default = 1

CVG

I index of order alpha = 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 I 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)

Maciej Pietrzak, Michal Seweryn, Grzegorz Rempala
Maintainer: Maciej Pietrzak pietrzak.20@osu.edu

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

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data(TCR.Data)
result <- i.inp(x, resample = 25)