Detecting Markov Random Fields Hidden in White Noise
Statistics Theory
2015-10-15 v2 Statistics Theory
Abstract
Motivated by change point problems in time series and the detection of textured objects in images, we consider the problem of detecting a piece of a Gaussian Markov random field hidden in white Gaussian noise. We derive minimax lower bounds and propose near-optimal tests.
Keywords
Cite
@article{arxiv.1504.06984,
title = {Detecting Markov Random Fields Hidden in White Noise},
author = {Ery Arias-Castro and Sébastien Bubeck and Gábor Lugosi and Nicolas Verzelen},
journal= {arXiv preprint arXiv:1504.06984},
year = {2015}
}
Comments
In the 2nd version we removed the part on path detection, which will appear on its own in a separate paper