CMStatistics 2020: Start Registration
View Submission - CMStatistics
Title: Two-sample testing on latent distance graphs with unknown link functions Authors:  Soumendra Lahiri - North Carolina State University (United States)
Minh Tang - North Carolina State University (United States) [presenting]
Yiran Wang - North Carolina State University (United States)
Abstract: A valid and consistent test is proposed for the hypothesis that two latent distance random graphs on the same vertex set have the same generating latent positions, up to some unidentifiable similarity transformations. The test statistic is based on first estimating the edge probabilities matrices by truncating the singular value decompositions of the averaged adjacency matrices in each population and then computing a Spearman rank correlation coefficient between these estimates. Experimental results on simulated data indicate that the test procedure has power even when there is only one sample from each population, provided that the number of vertices is not too small. Application on a dataset of neural connectome graphs showed that we can distinguish between scans from different age groups while application on a dataset of epileptogenic recordings.