IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v516y2019icp591-593.html
   My bibliography  Save this article

Response to Cho and Liu, “Sampling from complicated and unknown distributions: Monte Carlo and Markov chain Monte Carlo methods for redistricting”

Author

Listed:
  • Adler, William T.
  • Wang, Samuel S.-H.

Abstract

A question of legal significance is whether an enacted map of political districts is “typical.” Recent work has used Markov chain Monte Carlo (MCMC) methods to produce null distributions of maps in order to answer this question. A recent article by Cho and Liu critiques one particular implementation of MCMC for redistricting, that of Fifield et al. The goal of the present commentary is to draw attention to two facts omitted by Cho and Liu that, if included, would have severely weakened their conclusions. In particular, Cho and Liu point out that Fifield et al.’s algorithm fails to approximate a known target distribution, but neglect Fifield et al.’s use of parallel and simulated tempering, which greatly improves the approximation. Secondly, Cho and Liu argue that it is overly difficult to detect when Markov chains have mixed; they neglect to mention diagnostics used for this exact purpose in Fifield et al.

Suggested Citation

  • Adler, William T. & Wang, Samuel S.-H., 2019. "Response to Cho and Liu, “Sampling from complicated and unknown distributions: Monte Carlo and Markov chain Monte Carlo methods for redistricting”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 591-593.
    • Handle: RePEc:eee:phsmap:v:516:y:2019:i:c:p:591-593
    DOI: 10.1016/j.physa.2018.10.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118314055
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2018.10.057?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cho, Wendy K. Tam & Liu, Yan Y., 2018. "Sampling from complicated and unknown distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 170-178.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. F. Azizpour & F. Qaderi, 2020. "Optimization, modeling and uncertainty investigation of phenolic wastewater treatment by photocatalytic process in cascade reactor," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(7), pages 6315-6342, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:516:y:2019:i:c:p:591-593. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.