RStudio in the cloud, for dummies You can have your own cloud computing version of R, complete with RStudio. Why should you? It's cool! Plus, there's a lot more power out there than you can easily get on your own hardware. And, it's R in a web page. Montreal R Users Group See the general information page for workshop goals, format, what to expect, and what you need. You can reserve your spot by signing-up to the Montreal R User Group and registering for the workshops you are interested in. The workshops are free to attend (!) Statistics for a changing world: Google Public Data Explorer in Labs Last year, we released a public data search feature that enables people to quickly find useful statistics in search. More recently, we expanded this service to include information from the World Bank, such as population data for every region in the world. More and more public agencies, non-profits and other organizations are looking for ways to open up their data and expand global access to this kind of information. We want to help keep that momentum going, so today we're sharing a snapshot of some of the most popular public data search topics on Google.
Rob J Hyndman The latest issue of the IJF is a bumper issue with over 500 pages of forecasting insights. The GEFCom2014 papers are included in a special section on probabilistic energy forecasting, guest edited by Tao Hong and Pierre Pinson. This is a major milestone in energy forecasting research with the focus on probabilistic forecasting and forecast evaluation done using a quantile scoring method. Only a few years ago I was having to explain to energy professionals why you couldn’t use a MAPE to evaluate a percentile forecast. With this special section, we now have a tutorial review on probabilistic electric load forecasting by Tao Hong and Shu Fan, which should help everyone get up to speed with current forecasting approaches, evaluation methods and common misunderstandings. The section also contains a large number of very high quality articles showing how to do state-of-the-art density forecasting for electricity load, electricity price, solar and wind power.
R: Retrieving information from google using the RCurl package « "R" you ready? R: Retrieving information from google using the RCurl package 01Jan09 Lately I read the article Automatic Meaning Discovery Using Google by Cilibras and VitanyiIt which introduces the normalized google distance (NGD) as a measure of semantic relatedness of two search terms. knitr: Elegant, flexible and fast dynamic report generation with R Overview The knitr package was designed to be a transparent engine for dynamic report generation with R, solve some long-standing problems in Sweave, and combine features in other add-on packages into one package (knitr ≈ Sweave + cacheSweave + pgfSweave + weaver + animation::saveLatex + R2HTML::RweaveHTML + highlight::HighlightWeaveLatex + 0.2 * brew + 0.1 * SweaveListingUtils + more). This package is developed on GitHub; for installation instructions and FAQ's, see README.
Social Science Statistics Blog 28 April 2013 App Stats: Roberts, Stewart, and Tingley on "Topic models for open ended survey responses with applications to experiments" We hope you can join us this Wednesday, May 1, 2013 for the Applied Statistics Workshop. Molly Roberts, Brandon Stewart, and Dustin Tingley, all from the Department of Government at Harvard University, will give a presentation entitled "Topic models for open ended survey responses with applications to experiments". A light lunch will be served at 12 pm and the talk will begin at 12.15.
Forecasting Welcome to our online textbook on forecasting. This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. The book is written for three audiences: (1) people finding themselves doing forecasting in business when they may not have had any formal training in the area; (2) undergraduate students studying business; (3) MBA students doing a forecasting elective. We use it ourselves for a second-year subject for students undertaking a Bachelor of Commerce degree at Monash University, Australia.
Making Reproducible Research Enjoyable Note: this is a contributed article for the ICSA Bulletin and the basic idea can be summarized in this picture. It is hard to convince people to think about reproducible research (RR). There are two parts of difficulties: (1) tools used to be for experts only and (2) it is still common practice to copy and paste. For some statisticians, RR is almost equivalent to Sweave (R + LaTeX). The Endeavour — The blog of John D. Cook I help people make decisions in the face of uncertainty. Sounds interesting. I’m a data scientist. Win Vector Old tails: a crude power law fit on ebook sales We use R to take a very brief look at the distribution of e-book sales on Amazon.com. Read more… You don’t need to understand pointers to program using R
Mirai Solutions - XLConnect XLConnect is a powerful package that allows R users to read and write Excel files in a highly integrated manner from within R. It uses the Apache POI API (see as the underlying interface, so you may expect us to extend the current functionality of XLConnect accordingly in the future. One of the great things about XLConnect is its portability. You can use it across various platforms and operating systems - be it Windows 32 bit, Linux 64 bit or a Mac, you can run your favorite piece of XLConnect-code on all of them.
Fishing in the Bay » Blog Archive » Why I am in favour of logging A colleague recently brought to me some alternative fits he had done for a paper he was writing. The alternative fits looked very strange but had been strongly suggested by a referee. He was fitting a regression model to inter-country trade data and trying to explain patterns in terms of various measures of cultural fit. The referee was pointing to some papers in econometrics that had argued about the relative merits of multiplicative regression models fitted on the direct scale, rather than on the log-scale. The referee wanted a direct fit on the basis that the random errors may be more normal and additive on the direct scale.