Here I implemented in R some dithering algorithms:
- Floyd-Steinberg dithering
- Bill Atkinson dithering
- Jarvis-Judice-Ninke dithering
- Sierra 2-4a dithering
- Stucki dithering
- Burkes dithering
- Sierra2 dithering
- Sierra3 dithering
For each algorithm, I wrote a 2-dimensional convolution function (a matrix passing over a matrix); it is slow because I didn't implemented any fasting tricks. It can be easily implemented in C, then used...
Links to slides of 10+ talks at R Users Groups in Australia are provided below. Slides of the talks are downloadable at the links, including R codes if any. MelbURN: Melbourne Users of R Network: Experiences with using R in … Continue reading →
I'm working on a 3 part post on how to build, score and perform optimization with predictive models in R. Having done this type of work in IBM SPSS for a number of years, I wanted to replicate it in R. It's amazing how little is published on how to s...
R seems to have two byte code compilers: the Ra add-on module (and the accompanying "jit" package) and the "compiler" package came with the default installation. I wonder how they differentiate from each other and what the strengths and weaknesses...
In early May I had the opportunity to attend a workshop on using high performance computing in R hosted at Nimbios. I’ve been meaning to write a summary of the meeting ever since but got sidetracked by various other projects. Since a collaborator recently asked for meeting notes I finally took the time to write
As September draws nearer, my mind inevitably turns away from my lofty (and largely unmet) summer research goals, and toward teaching. This semester I will be trying out a teaching technique using live data collection and analysis as a tool to encourage student engagement. The idea is based on the electronic polling technology known as 
Most elementary statistical inference algorithms assume that the data can be modeled by a set of linear parameters with a normally distributed noise component. A new class of algorithms called support vector machine (SVM) remove such constraint. rea...
Okay so you want to forecast in R, but don't want to manually find the best model and go through the drudgery of plotting and so on. I have recently found the perfect function for you. Its called auto.arima and it automatically fits the bes...
<< My review of Day 1.
I am summarizing all of the days together since each talk was short, and I was too exhausted to write a post after each day. Due to the broken-up schedule of the KDD sessions, I group everything together instead of switching back and forth among a dozen different topics. By far the most enjoyable...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
