A Practical Example of Calculating Padé Approximant Coefficients Using R
I recently had the opportunity to use Padé approximants. There is a lot of good information available on line on the theory and applications of using Padé approximants, but I had trouble finding a good example explaining just how to calculate the co-efficients.

Spark Reaches for the Holy Grail: Federated Queries
The major data warehouse players – IBM, Oracle, SAS, Teradata – set the bar for federation, and the solutions from these companies allow seamless access to data from multiple, external sources via the vendor’s SQL interfaces and APIs. In other words, if you have JSON files, DB2 data, XML, Sybase data… with these federation technologies, you can query across all these sources in a single SQL statement. Of course, these solutions have a cost, both in terms of software licenses and specialized engineers. Apache hopes to alter the landscape with its Open Source Spark project.

Beautiful table-outputs: Summarizing mixed effects models
The current version 1.8.1 of my sjPlot package has two new functions to easily summarize mixed effects models as HTML-table: sjt.lmer and sjt.glmer. Both are very similar, so I focus on showing how to use sjt.lmer here.

R Recipe: RStudio and UNC Paths
RStudio does not like Uniform Naming Convention (UNC) paths. This can be a problem if, for example, you install it under Citrix. The solution is to create a suitable environment file. This is what worked for me: I created an .Renviron file in my Documents folder on the Citrix remote drive.

Measures of Predictive Models: Sensitivity and Specificity
There are many ways to measure how well a statistical model predicts a binary outcome. Three very common measures are accuracy, sensitivity, and specificity.