Every two years we award a prize for the best paper published in the International Journal of Forecasting. It is now time to identify the best paper published in the IJF during 2014 and 2015. There is always about 18 months delay after the publication period to allow time for reflection, citations, etc. The prize is US$1000 plus an engraved plaque. I will present the prize at the ISF in Cairns in late June.
Nominations are invited from any reader of the IJF. Each person may nominate up to three papers, but you cannot nominate a paper that you have coauthored yourself. Papers coauthored by one of the six editors (Hyndman, Kapetanios, McCracken, Önkal, Ruiz, or van Dijk) are not eligible for the prize. All nominated papers are to be accompanied by a short statement (up to 200 words) from the nominator, explaining why the paper deserves an award.
You can see all the papers published in the period 2014-2105 on Google Scholar. You can also download a spreadsheet of the relevant papers with citations as counted by Scopus. Scopus does not cover every published journal, so the citation counts are underestimates, but they give some general guide as to which papers have attracted the attention of researchers. Google Scholar includes far more citations including working papers, but there may be some double counting.
Of course, a good paper does not always get noticed, so don’t let the citation count sway you too much in nominating what you consider to be the best IJF paper from this period.
Nominations should be sent by email to me by 30 April 2017.
In what is now a roughly annual event, the forecast package has been updated on CRAN with a new version, this time 8.0.
A few of the more important new features are described below. Continue reading →
We are still looking for a few more invited sessions for the International Symposium on Forecasting, to be held in Cairns, Australia, 25-28 June 2017. Continue reading →
Courtesy of Tourism Tropical North Queensland
We know Australia is a long way to come for many forecasters, so we are making it easy for you to bring your families along to the International Symposium on Forecasting and have a vacation at the same time.
During the International Symposium on Forecasting, there will be a social program organized for family and friends. Continue reading →
AusMacroData is a new website that encourages and facilitates the use of quantitative, publicly available Australian macroeconomic data. The Australian Macro Database hosted at ausmacrodata.org provides a user-friendly front end for searching among over 40000 economic variables and is loosely based on similar international sites such as the Federal Reserve Economic Database (FRED). Continue reading →
The International Symposium on Forecasting is a little unusual for an academic conference in that it has always had a strong presence of forecasters working in business and industry as well as academic forecasters, mostly at universities. We value the combination and interaction as it helps the academics understand the sorts of problems facing forecasters in practice, and it helps practitioners stay abreast of new methods and developments coming out of forecasting research.
For the next ISF to be held in Cairns, Australia, in June 2017, we have a great line-up of forecast practitioners discussing some of their forecasting challenges (and solutions). These speakers and their topics are listed below. Continue reading →
From my email today
You use an illustration of a seasonal arima model:
I would like to simulate data from this process then fit a model… but I am unable to find any information as to how this can be conducted… if I set phi1, Phi1, theta1, and Theta1 it would be reassuring that for large n the parameters returned by
Arima(foo,order=c(1,1,1),seasonal=c(1,1,1)) are in agreement…
arima.sim() won’t handle seasonal ARIMA models. I wrote
simulate.Arima() to handle them, but it is designed to simulate from a fitted model rather than a specified model. However, you can use the following code to do it. It first “estimates” an ARIMA model with specified coefficients. Then simulates from it.
model <- Arima(ts(rnorm(100),freq=4), order=c(1,1,1), seasonal=c(1,1,1),
fixed=c(phi=0.5, theta=-0.4, Phi=0.3, Theta=-0.2))
foo <- simulate(model, nsim=1000)
fit <- Arima(foo, order=c(1,1,1), seasonal=c(1,1,1))
Professor Tao Hong has generously funded a new prize for the best IJF paper on energy forecasting, to be awarded every two years. The first award will be for papers published in the International Journal of Forecasting during the period 2013-2014. The prize will be US$1000 plus an engraved plaque. The award committee is Rob J Hyndman, Pierre Pinson and James Mitchell.
Nominations are invited from any reader of the IJF. Each person may nominate up to three papers, but you cannot nominate a paper that you have coauthored yourself. Papers coauthored by Tao Hong or one of the award committee are not eligible for the prize. All nominations are to be accompanied by a short statement (up to 200 words) from the nominator, explaining why the paper deserves an award.
You can see the relevant papers published in the period 2013-2014 on Google Scholar. Of course, a good paper does not always get noticed, so don’t let the citation count sway you too much in nominating what you consider to be the best IJF paper from this period.
Nominations should be sent to me by email by 8 February 2017.
I seem to be getting an increasing number of submissions where the author has clearly not bothered to actually check that the paper was submitted correctly. Here is a rejection letter I wrote today.
I am writing concerning manuscript #INTFOR_16xxxxx entitled “xxxxxxxxxxxxxxxx” which you submitted to the International Journal of Forecasting.
Thank you for this submission, but as it consists entirely of the IJF author guidelines, it is not suitable for publication in the IJF. We publish original research, not author guidelines. Perhaps the Journal for Guidelines would be an appropriate outlet.
In future, when you are asked to check the pdf of your paper, you might find it useful to actually do so, rather than just claim to have done so. That way, you might avoid this kind of mistake.
In the light of the comments above, I have chosen not to publish your manuscript in the International Journal of Forecasting. I know this will be disappointing to you, but we receive a large number of submissions and can only publish a small percentage of them.
Thank you for considering the International Journal of Forecasting for the publication of your research. I hope the outcome of this specific submission will not discourage you from the submission of future manuscripts.
Prof. Rob J Hyndman
Editor-in-Chief, International Journal of Forecasting
I’ve added a couple of new functions to the forecast package for R which implement two types of cross-validation for time series. Continue reading →