A new version of rasterVis is available at CRAN. This version includes several bug fixes and a new method to …Continuar leyendo »

R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. One of my main motivations to install R is Sweave. The Sweave is a literate programming language which integrates LaTeX and R code. The main idea of the Sweave is to combine data analysis code...

In the natural sciences, it is common to have incomplete or unevenly sampled time series for a given variable. Determining cycles in such series is not directly possible with methods such as Fast Fourier Transform (FFT) and may require some degree of interpolation to fill in gaps. An alternative is the Lomb-Scargle method (or...

Here’s a video how the modFit function from the FME package optimizes parameters for an oscillation. A Nelder-Mead-optimizer (R function optim) finds the best fitting parameters for an undampened oscillator. Minimum was found after 72 iterations, true parameter eta was -.05: Evolution of parameters in optimization process from Felix Schönbrodt on Vimeo. More on estimating

Yesterday’s post started to explore the nice additions which the new C++11 standard is bringing to the language. One particularly interesting feature are lambda functions which resemble the anonymous functions R programmers have enjoyed all along...

One issue I continuously encounter when starting to work with a new dataset is that of the codebook. In general, I prefer to load a codebook into R like any other data source, specifically as a data frame. And ideally, one data frame to provides the variable names with descriptions and any other meta data available, and a separate...

The go-to bible for this data scientist and many others is The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Each of the authors is an expert in machine learning / prediction, and in some cases invented the techniques we turn to today to make sense of big data: ensemble...