In my last two posts, I have tinkered with the 'gam' package to create heat maps for individual umpire strike zones. I went ahead and grabbed Joe West's data (which has a lot more pitches than Bruce Froemming in it, since Froemming's data is only from...
The San Francisco Bay Area ACM runs several courses on data mining and machine learning with R. Machine Learning 101 deals primarily with supervised learning problems, and Machine Learning 102 covers unsupervised learning and fault detection. Machine Learning 101 & 102 were most recently presented by Mike Bowles & Tricia Hoffman in September, and the lecture notes and class...
In recent weeks, we've explored methods to fit logistic regression models when a state of quasi-complete separation exists. We considered Firth's penalized likelihood approach, exact logistic regression, and Bayesian models using Markov chain Monte Ca...
A friend recently bought The R Book and I said I would tell him of problems that I’ve noticed with it. You can eavesdrop. Page 4 The word “library” is used instead of “package”. This (common) error substantially raises the blood pressure of some people — probably to an unwarranted extent. An R package is … Continue reading...
The Global Historical Climate Network (GHCN) is in it’s beta stage. On of the stated goals of the project is to improve the metadata that is provided for the station data. Over the past few months several independent volunteers have been focusing on the issue of station metadata, each with their own focus. Ron Broberg 
Chapter 4 of Using R for Introductory Statistics gets us started working with multivariate data. The question is: what are the relationships among the variables? One way to go about answering it is by pairwise comparison of variables. Another techniq...
Chapter 4 of Using R for Introductory Statistics gets us started working with multivariate data. The question is: what are the relationships among the variables? One way to go about answering it is by pairwise comparison of variables. Another technique is to divide the data into categories by the values of some variables and...
See also NEURAL NETWORKS.
In this past June's issue of R journal, the 'neuralnet' package was introduced. I had recently been familiar with utilizing neural networks via the 'nnet' package (see my post on Data Mining in A Nutshell) but I find the neuralnet package more useful because it will allow you to actually plot...
Just two hours ago, Professor John Fox has announced on the R-help mailing list of a new (second) edition to his book “An R and S Plus Companion to Applied Regression”, now title . “An R Companion to Applied Regression, Second Edition”. John Fox is (very) well known in the R community for many contributions to R, including the...
Describing multivariate data is not easy. Especially, if you think that statisticians have not developed any new tools after the ANOVA and principal component analysis (PCA). For social and experimental scientists the most important new technique are structural equation models that combine measurement models (that substitute reliability analysis and PCA) and structural models (that substitute
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
