README.md

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Overview of the nevada package

The package nevada (NEtwork-VAlued Data Analysis) is an R package for the statistical analysis of network-valued datasets. In this setting, a sample is made of statistical units that are networks themselves. The package provides a set of matrix representations for networks so that network-valued data can be transformed into matrix-valued data. Subsequently, a number of distances between matrices is provided as well to quantify how far two networks are from each other and a number of distance-based statistics is proposed for testing equality in distribution between samples of networks using exact permutation testing procedures. The implementation is largely made in C++ and the matrix of inter- and intra-sample distances is pre-computed, which alleviates the computational burden often associated with permutation tests. In details:

See the vignette NEtwork-VAlued Data Analysis for the details of each function.

Installation

You can install nevada from github with:

# install.packages("devtools")
devtools::install_github("astamm/nevada")

It relies on the igraph package. If you encounter bugs or for questions and comments, please contact the maintainer of the package.

Usage

Example 1

In this first example, we compare two populations of networks generated according to two different models (Watts-Strogatz and Barabasi), using the modularity matrix representation of networks, the Hamming distance to compare single networks and the average statistic to summarize information and perform the permutation test.

n <- 10L
x <- nevada::nvd("smallworld", n)
y <- nevada::nvd("pa", n)
t1 <- nevada::test2_global(x, y, representation = "modularity")
t1$pvalue
#> [1] 0.0009936031

Example 2

In this second example, we compare two populations of networks generated according to the sane model (Watts-Strogatz), using once again the modularity matrix representation of networks, the Hamming distance to compare single networks and the average statistic to summarize information and perform the permutation test.

n <- 10L
x <- nevada::nvd("smallworld", n)
y <- nevada::nvd("smallworld", n)
t2 <- nevada::test2_global(x, y, representation = "modularity")
t2$pvalue
#> [1] 0.2227718


ilovato/nevada documentation built on May 30, 2019, 9:47 p.m.