A great new feature has been added to Google Scholar Citations. For those authors who have set up a citations page, it is now possible to get email alerts for any new articles they publish, or for any new citations of their articles. So you can track citations to your own work this way, and stay up-to-date with key authors in your field. Setting up a Google Citations page is super-easy and was already worth doing. This new functionality is another reason to do it. After all, as researchers we want people to read our stuff, so we might as well make it as easy as possible for people to find what we write. To set up your Google Citations page, go to scholar.google.com/citations. To follow an author, find their citations page and look for the “Follow this author” box at the top right of the page. Hopefully, Google will add RSS feeds as an option in the future as I’d much rather get alerts that way then by yet more email in my inbox.
Posts Tagged ‘references’:
The art of R programming
This is a gem of a book. It will become the book I give PhD students when they are learning how to write good R code. That is, if I ever see it again. I had hoped to write a review of it, but I haven’t seen it since it arrived in the mail a couple of weeks ago because a research student or research assistant has always had it on loan. I guess that’s a testament to how useful it is.
Researcher portals
A researcher portal is a website that attempts to list all the publications of a given researcher. Some portals also allow sharing papers, interacting with other researchers, calculating citation statistics, etc. Every researcher wants their work read and cited, so these websites can be useful tools for getting your work noticed. They can also function as a de facto home page if you don’t already have a personal website. Conversely, they can be a good way to find new work by researchers in your field. However, unless a site provides a relatively complete list of your publications, and covers a large proportion of the research community in your discipline, it is of limited value.
Switching from JabRef to Mendeley
Mendeley has a lot more facilities than JabRef, and I’ve recommended that everyone in my research group switch to Mendeley. However, if you’ve been using JabRef for a while then you won’t want to lose all your pdf links and other information stored in JabRef. Here are a couple of ideas to make the conversion simpler.
Use Mendeley to manage your references
Every researcher collects large numbers of papers, references, and notes, and it is important to have a good system to keep them all organized. For many years I had several thousand papers all numbered and stored in filing cabinets, with a JabRef database providing an index to them. These days, it’s much easier to have everything stored electronically, and so I have accumulated many pdfs (about 1300 so far) of published articles. But the problem of being able to find something fast is still important. Mendeley is a free software tool for managing your reference database. It actually solves many problems simultanéously and is likely to become an important part of how I work.
Recommended survey papers
Survey articles are particularly helpful in getting a foothold in a new research area, or in looking for important papers that you may have overlooked. Whatever area of research you are in, look out for survey papers and journals dedicated to publishing survey papers.
How to avoid annoying a referee
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.stackexchange.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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Your name is your brand
As a researcher, you want to become known as an expert in your field. You need people to recognize your name and associate it with your research. Consequently, it is important to be consistent in the name you use on publications. For example, I could write under “R Hyndman”, “R J Hyndman”, “Rob Hyndman”, “Rob J Hyndman”, etc. I’ve chosen the last of these and I try to use it on all publications. Unfortunately, some journals insist on only initials, in which case I become “R J Hyndman”. In other cases, a coauthor handles all the correspondence with the journal and, despite my requests, they just list me as “R Hyndman” or “Rob Hyndman”. So I have not achieved consistency, but I try. Researchers from countries with more elaborate naming conventions than the Western tradition will have even more options, and so it is even more important to aim for consistency in publications. Consistency is also important when others are searching for one of your papers. If you have changed your name, or you use two very different names, then it will be harder for other researchers to find the paper of yours that they are looking for. This can be a problem when people have changed their name at marriage,
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Econometrics and R
Econometricians seem to be rather slow to adopt new methods and new technology (compared to other areas of statistics), but slowly the use of R is spreading. I’m now receiving requests for references showing how to use R in econometrics, and so I thought it might be helpful to post a few suggestions here. A useful on-line and free resource is “Econometrics in R” by Grant Farnsworth. It covers some common econometric methods including heteroskedasticity in regression, probit and logit models, tobit regression, and quantile regression. In the time series area, it covers ARIMA, ARFIMA, ARCH and GARCH models, as well as a few of the standard tests for unit roots and autocorrelation. It’s brief but it does provide code that will help people familiar with econometrics to get started using R. If you are prepared to pay, an excellent book is Kleiber and Zeilis’s Applied Econometrics with R. It covers similar ground to Farnsworth but in more detail. This is the book I usually recommend to anyone with an econometrics background who is wanting to get started with R. It would also be very suitable for someone studying econometrics at about upper undergraduate level. Achim Zeileis is a well-known expert in R programming, so you can be sure the code
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Academic citations in the popular press
It is very unusual for a newspaper article to cite an academic paper, unless it is in Nature, Science or the Lancet. Mostly, what we write is too technical and assumes too much background knowledge for it to be accessible to anyone but specialists. So I was pleasantly surprised to find a reference to the International Journal of Forecasting in a recent Wall Street Journal article. It is a citation of a 1996 article, so in terms of scientific research it is a bit like quoting the Magna Carta, but a citation nevertheless. I once tried to get newspaper coverage of a special issue of the IJF on forecasting the US Presidential election. It was published about four months before the 2008 elections. If anything was going to attract the attention of the popular press, surely this was the topic! Alas, all we managed was a short piece on a research news website although there were copious articles on predicting the election result based on less valid methods. Even forecasting the recent world cup didn’t get any serious attention, despite some excellent (albeit unpublished) work over at kaggle.com. Paul the Octopus had tens of thousands of news articles, but the careful statistical modelling at kaggle had none at all that
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Rob J Hyndman