Bayesian computing, methods and applications (and Elsevier)

I received an email this weekend calling for submissions to a special issue of Computational Statistics and Data Analysis on the special topic Bayesian computing, methods and applications, edited by Cathy Chen, David Dunson, Sylvia Frühwirth-Schnatter, and Stephen Walker.   The theme is

The last two decades have seen an explosion in the popularity and use of Bayesian methods, largely as a result of the advances in sampling based approaches to inference. At the same time, important advances and developments in methodology have coincided with highly sophisticated breakthroughs in computational techniques. Consequently, practitioners are increasingly turning to Bayesian methods so as to effectively tackle more complex and realistic models and problems, particularly as richer sources of data continue to become available. The primary aim of the issue is to illustrate and showcase recent advances in Bayesian computation and inferential methods, as well as highlight their application to empirical problems in a broad range of areas, including econometrics, biology, finance and medicine, amongst many others. Methodological contributions that highlight recent developments in Bayesian computing are strongly encouraged.

The papers should have a computational or advanced data analytic component in order to be considered for publication. Authors who are uncertain about the suitability of their papers should contact the special issue editors. All submissions must contain original unpublished work not being considered for publication elsewhere. Submissions will be refereed according to standard procedures for Computational Statistics and Data Analysis. The deadline for submissions is 30 June 2012.

Unfortunately, this journal is published by Elsevier, the costly much too costly publisher [Computational Statistics and Data Analysis costs for instance 2,763 euros per year for institutions and libraries!, Journal of Multivariate Analysis is 2,704 euros…] and, since I am completely in agreement with the position, I have signed the Cost of Knowledge pledge a few weeks ago [although I do not yet appear on the list], meaning I now abstain from supporting the extremely unbalanced business model of Elsevier though publishing, reviewing, or (a)editing in one of the journals it publishes. (Which means I refuse referring on this sole ground about once a week now.) Even though Elsevier published a letter to mathematicians a few weeks ago, I however doubt they can modify their business model so drastically as to get down to average prices for their journals. Unless the pressure from the community is so committed and shared that the flow of submissions dries out, which I doubt will occur on a short time-scale. (The impact of a reduced submission pool on citation indices and impact factors is on another scale…) Jean-Michel pointed me to this arXiv report [to appear in Notices of the American Mathematical Society] by Douglas Arnold and Henry Cohn on the Cost of Knowledge boycott (analysed by mathematicians, not statisticians). It seems that the boycott has not impacted as much the statisticians’ community, judging from the number of signatures registered so far.

As a coincidence, I read today in the Guardian that the Wellcome Trust is pulling its weight in support of open source publishing, threatening to withdraw funding from researchers who do not “ensure that results are freely available to the public within six months of first publication”. Elsevier’s statement is not encouraging, though: “we will also remain committed to the subscription model. We want to be able to offer our customers choice, and we see that, in addition to new models the subscription model remains very much in demand.” (I do not see the connection between high subscription rates and choice, nor a proof that anyone demands high subscription rates!) Another coincidence is that I also got an email about The Open Statistics & Probability Journal, which is a free, peer reviewed, on-line journal. Which shows that some companies have found a way to manage a business model that is compatible with open access, if not a good solution in my opinion: just charge the authors $400 per published paper…

5 Responses to “Bayesian computing, methods and applications (and Elsevier)”

  1. […] and Princeton, resp., published in the American Journal of Preventive Medicine. (Incidentally, an Elsevier journal, making the open access to the paper the most surprising!) The first thing in the paper is […]

  2. Automatic blog commenting tool…

    […]Bayesian computing, methods and applications (and Elsevier) « Xi'an's Og[…]…

  3. […] and bad) journals would be the Hell of non-stop reference letters. I definitely prefer to referee (except for Elsevier!) and even more being a journal editor, because I can get an idea of the themes in the field and […]

  4. Not only do you appear on the list, you appear there twice!

    Christian P. Robert
    Universite Paris-Dauphine – Mathematics
    won’t publish
    won’t referee
    won’t do editorial work

    Christian Robert
    Universite Paris-Dauphine – Statistics
    won’t publish
    won’t referee
    won’t do editorial work
    I have already started refusing refereeing papers for Elsevier. I favour nonprofit editors for professional societies.

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