@inproceedings{79e3496241724056ba0e17b05d454cca,
title = "Speeding up Algebraic-Based Sampling via Permutations",
abstract = "Algebraic sampling methods are a powerful tool to perform hypothesis tests on conditional spaces. We analyse the link of the sampling method introduced in[6] with permutation tests and we exploit this link to build a two-step sampling procedure to perform two-sample comparisons for non-negative discrete exponential families. We thus establish a link between standard permutation and algebraic-statistics-based sampling. The proposed method reduces the dimension of the space on which the MCMC sampling is performed by introducing a second step in which a standard Monte Carlo sampling is performed. The advantages of this dimension reduction are verified through a simulation study, showing that the proposed approach grants convergence in the least time and has the lowest mean squared error.",
keywords = "Conditional tests, Discrete exponential families, Markov basis, Markov chain monte carlo",
author = "Crucinio, \{Francesca Romana\} and Roberto Fontana",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 4th Conference of the International Society for Nonparametric Statistics, ISNPS 2018 ; Conference date: 11-06-2018 Through 15-06-2018",
year = "2020",
month = jan,
day = "1",
doi = "10.1007/978-3-030-57306-5\_14",
language = "English",
isbn = "9783030573058",
series = "Springer Proceedings in Mathematics and Statistics",
publisher = "Springer",
pages = "145--155",
editor = "\{La Rocca\}, Michele and Brunero Liseo and Luigi Salmaso",
booktitle = "Nonparametric Statistics - 4th ISNPS 2018",
}