## geom_smooth: method="auto" and size of largest group is <1000, so using## loess. Use 'method = x' to change the smoothing method. I remember my dad telling me that when he was at Northwestern in the mid-70s, the team...

Manfred Schroeder touches on the topic of percolation a number of times in his encyclopaedic book on fractals (Schroeder, M. (1991). Fractals, Chaos, Power Laws: Minutes from an Infinite Paradise. W H Freeman & Company.). Percolation has numerous practical applications, the most interesting of which (from my perspective) is the flow of hot water through

We're very excited to formally announce that Revolution R Enterprise 7 is here! This release includes the latest release of Open Source R (R 3.0.2). It brings R and the massively-parallel R functions from Revolution Analytics to Cloudera and Hortonworks in-Hadoop, and in-database on Teradata. It also brings a new drag-and-drop user interface via integration with Alteryx, and a...

If you read my post about Fast Bayesian Inference with INLA you might wonder which models are included within the class of latent Gaussian models (LGM), and can therefore be fitted with INLA. Next I will give a general definition about LGM and later I will describe three completely different examples that belong to this

This a final reminder about the October 15 deadlines for MCMSki IV: First, the early bird rate for the registration ends up on October 15. Second, the young investigator travel support can only be requested up to October 15 as well. (For those waiting for the decision about the support to register, the registration deadline will be

There are lots of R engines emerging! I’ve interviewed members of each of the teams involved in these projects. In part 1 of this series, we covered the motivation of each project. This part looks at the technical achievements and new features. Many of the innovations are performance improvements, reflecting the primary goal of several

We're thrilled to have John Wallace and Tess Nesbitt from DataSong join our Fall webinar series tomorrow, with a great presentation on time to event models. If you're trying to predict when an event will occur (for example, a consumer buying a product) or trying to infer why events occur (what were the factors that led to a component...