A principled (and practical) test for network comparison

07/23/2021
by   Gecia Bravo Hermsdorff, et al.
0

How might one test the hypothesis that graphs were sampled from the same distribution? Here, we compare two statistical tests that address this question. The first uses the observed subgraph densities themselves as estimates of those of the underlying distribution. The second test uses a new approach that converts these subgraph densities into estimates of the graph cumulants of the distribution. We demonstrate – via theory, simulation, and application to real data – the superior statistical power of using graph cumulants.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/15/2021

A practical test for a planted community in heterogeneous networks

One of the fundamental task in graph data mining is to find a planted co...
research
01/29/2021

A Practical Two-Sample Test for Weighted Random Graphs

Network (graph) data analysis is a popular research topic in statistics ...
research
04/15/2020

On uniform consistency of nonparametric tests II

For Kolmogorov test we find natural conditions of uniform consistency of...
research
11/07/2019

Improving Power of 2-Sample Random Graph Tests with Applications in Connectomics

In many applications, there is an interest in testing whether two graphs...
research
11/05/2020

Motif Estimation via Subgraph Sampling: The Fourth Moment Phenomenon

Network sampling is an indispensable tool for understanding features of ...
research
03/30/2020

Subgraph densities in a surface

Given a fixed graph H that embeds in a surface Σ, what is the maximum nu...
research
09/05/2018

A Differentially Private Wilcoxon Signed-Rank Test

Hypothesis tests are a crucial statistical tool for data mining and are ...

Please sign up or login with your details

Forgot password? Click here to reset