We are currently advertising for three academic positions, suitable for recent PhD graduates. Lecturer (Applied Statistics or Operations Research) Five-year position with MAXIMA and the School of Mathematical Sciences Two positions available. Applications close 31 October. More information. Lecturer (Econometrics/Business Statistics) Continuing position with the Department of Econometrics and Business Statistics Applications close 31 January 2014. More information. Please don’t send any questions to me. Click the “More information” links and follow the instructions.
Posts Tagged ‘statistics’:
The International Journal of Forecasting is calling for papers on probabilistic energy forecasting. Here are the details (taken from Tao Hong’s blog).
I’ve been getting emails asking questions about my upcoming course on Forecasting using R. Here are some answers.
The publishing platform I set up for my forecasting book has now been extended to cover more books and greater functionality. Check it out at www.otexts.org.
The following video has been produced to advertise my upcoming course on Forecasting with R, run in partnership with Revolution Analytics.
I’ve had several emails recently asking how to forecast daily data in R. Unless the time series is very long, the easiest approach is to simply set the frequency attribute to 7. y < — ts(x, frequency=7) Then any of the usual time series forecasting methods should produce reasonable forecasts. For example library(forecast) fit < — ets(y) fc <- forecast(fit) plot(fc)
The “Monash Academy for Cross and Interdisciplinary Mathematical Applications” (MAXIMA) is a new research centre that aims to maximise the potential of mathematics to deliver impact to society. It will be led by Kate Smith-Miles. I will also be involved along with several other mathematicians at Monash. Our mission at MAXIMA is to find solutions to 21st century problems by dismantling mathematical barriers. MAXIMA will be launched on 25 September at a public lecture on “The Role of Embedded Optimization in Smart Systems and Products”. More details at community.monash.edu/maxima
I am teaming up with Revolution Analytics to teach an online course on forecasting with R. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and forecast evaluation techniques such as cross-validation. I will talk about some of my consulting experiences, and explain the tools in the forecast package for R. The course will run from 21 October to 4 December, for two hours each week. Participants can network and interact with other practitioners through an online community.
This week I’ve been at the R Users conference in Albacete, Spain. These conferences are a little unusual in that they are not really about research, unlike most conferences I attend. They provide a place for people to discuss and exchange ideas on how R can be used. Here are some thoughts and highlights of the conference, in no particular order.
Akaike’s Information Criterion (AIC) is a very useful model selection tool, but it is not as well understood as it should be. I frequently read papers, or hear talks, which demonstrate misunderstandings or misuse of this important tool. The following points should clarify some aspects of the AIC, and hopefully reduce its misuse.