After entirely too long, I am happy to announce the beta release of boolean3, an R package for modeling causal complexity. The package can be downloaded at the following links: Unix/Linux: boolean3_3.0.20.tar.gz Windows: boolean3_3.0.20.zip (Please let me know if you have any … Continue reading →
Posts Tagged ‘ code ’
Doing Bayesian Data Analysis now in JAGS
Around Christmas time I presented my first impressions of Kruschke’s Doing Bayesian Data Analysis. This is a very nice book but one of its drawbacks was that part of the code used BUGS, which left mac users like me stuck. … Continue reading →
Graphing Twitter friends/followers with R (updated yet again)
Those of you following my occasional updates here know that I have previously posted code for graphing Twitter friend/follower networks using R (post #1. post #2). Kai Heinrich was kind enough to send me some updated code for doing so using a newer version of the extremely useful twitteR package. His very crisp, yet...
R pitfall #3: friggin’ factors
I received an email from one of my students expressing deep frustation with a seemingly simple problem. He had a factor containing names of potato lines and wanted to set some levels to NA. Using simple letters as example names … Continue reading →
Book shoppin’…
I honestly have no book on R programming. In fact I have not a single book on programming at all (my coding proves that ;x). I am pretty sure that I am gonna order (just did!) that book. You can get a look of Matloff’s text here (= pdf for ya)
Using neural network for regression
Artificial neural networks are commonly thought to be used just for classification because of the relationship to logistic regression: neural networks typically use a logistic activation function and output values from 0 to 1 like logistic regression. ...
Train neural network in R, predict in SAS
This R code fits an artificial neural network in R and generates Base SAS code, so new records can be scored entirely in Base SAS. This is intended to be a simple, elegant, fast solution. You don’t need SAS Enterprise Miner, IML, or any other spe...
Confidence interval diagram in R
This code shows how to easily plot a beautiful confidence interval diagram in R. First, create a data frame (R’s representation of a table) with three columns. There are two rows for two confidence intervals, but you can have as many rows as you ...
Lattice when modeling, ggplot when publishing
When working in research projects I tend to fit several, sometimes quite a few, alternative models. This model fitting is informed by theoretical considerations (e.g. quantitative genetics, experimental design we used, our understanding of the process under study, etc.) but … Continue reading →
Model decision tree in R, score in Base SAS
This code creates a decision tree model in R using party::ctree() and prepares the model for export it from R to Base SAS, so SAS can score new records. SAS Enterprise Miner and PMML are not required, and Base SAS can be on a separate machine from R be...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
