A blog by Rob J Hyndman 

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Posts Tagged ‘reproducible research’:


How to avoid annoying a referee

Published on 22 October 2010

It’s not a good idea to annoy the ref­er­ees of your paper. They make rec­om­men­da­tions to the edi­tor about your work and it is best to keep them happy. There is an inter­est­ing dis­cus­sion on stats​.stack​ex​change​.com on this sub­ject. This inspired my own list below. Explain what you’ve done clearly, avoid­ing unnec­es­sary jar­gon. Don’t claim your paper con­tributes more than it actu­ally does. (I ref­er­eed a paper this week where the author claimed to have invented prin­ci­pal com­po­nent analy­sis!) Ensure all fig­ures have clear cap­tions and labels. Include cita­tions to the referee’s own work. Obvi­ously you don’t know who is going to ref­eree your paper, but you should aim to cite the main work in the area. It places your work in con­text, and keeps the ref­er­ees happy if they are the authors. Make sure the cited papers say what you think they say. Sight what you cite! Include proper cita­tions for all soft­ware pack­ages. If you are unsure how to cite an R pack­age, try the com­mand citation(“packagename”). Never pla­gia­rise from other papers — not even sen­tence frag­ments. Use your own words. I’ve ref­er­eed a the­sis which had slabs taken from my own lec­ture notes includ­ing the typos. Don’t pla­gia­rise from your own papers. Either ref­er­ence

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Replications and reproducible research

Published on 2 December 2009

Repro­ducible research One of the best ways to get started with research in a new area is to try to repli­cate some exist­ing research. In doing so, you will usu­ally gain a much bet­ter under­stand­ing of the topic, and you will often dis­cover some prob­lems with the research, or develop ideas that will lead to a new research paper. Unfor­tu­nately, a lot of papers are not repro­ducible because the data are not made avail­able, or the descrip­tion of the meth­ods are not detailed enough. The good news is that there is a grow­ing move amongst fund­ing agen­cies and jour­nals to make more research repro­ducible.  Peng, Dominici and Zeger (2006) and Koenker and Zeileis (2009) pro­vide help­ful dis­cus­sions of new tools (espe­cially Sweave) for mak­ing research eas­ier to repro­duce. The Inter­na­tional Jour­nal of Fore­cast­ing is also encour­ag­ing researchers to make their data and com­puter code avail­able in order to allow oth­ers to repli­cate the research. I have just writ­ten an edi­to­r­ial on this topic which will appear in the first issue of 2010. Here is an excerpt from the arti­cle: As the lead­ing jour­nal in fore­cast­ing, the IJF has a respon­si­bil­ity to set research stan­dards. So, a cou­ple of years ago, we started ask­ing authors to make their data

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