A Fast MCMC for the Uniform Sampling of Binary Matrices with Fixed Margins

04/08/2019
by   Guanyang Wang, et al.
0

Uniform sampling of binary matrix with fixed margins is an important and difficult problem in statistics, computer science, ecology and so on. The well-known swap algorithm would be inefficient when the size of the matrix becomes large or when the matrix is too sparse/dense. Here we propose the Rectangle Loop algorithm, a Markov chain Monte Carlo algorithm to sample binary matrices with fixed margins uniformly. Theoretically the Rectangle Loop algorithm is better than the swap algorithm in Peskun's order. Empirically studies also demonstrates the Rectangle Loop algorithm is remarkablely more efficient than the swap algorithm.

READ FULL TEXT

page 10

page 11

page 14

research
04/08/2019

A Fast Scheme for the Uniform Sampling of Binary Matrices with Fixed Margins

Uniform sampling of binary matrix with fixed margins is an important and...
research
09/02/2018

A fast Metropolis-Hastings method for generating random correlation matrices

We propose a novel Metropolis-Hastings algorithm to sample uniformly fro...
research
12/07/2021

fastball: A fast algorithm to sample binary matrices with fixed marginals

Many applications require randomly sampling binary graphs with fixed deg...
research
04/14/2021

Novel Matrix Hit and Run for Sampling Polytopes and Its GPU Implementation

We propose and analyze a new Markov Chain Monte Carlo algorithm that gen...
research
06/26/2020

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions

The Metropolis algorithm is arguably the most fundamental Markov chain M...
research
12/06/2020

FPRAS Approximation of the Matrix Permanent in Practice

The matrix permanent belongs to the complexity class #P-Complete. It is ...
research
01/01/2018

Computation of Maximal Determinants of Binary Circulant Matrices

We describe algorithms for computing maximal determinants of binary circ...

Please sign up or login with your details

Forgot password? Click here to reset