In this post I extend the multiplicative Bayesian sensory profiling model with effects for rounds and sessions. Is is not a difficult extension, but it brings the need for informative priors into the model. I do believe round and session effects exist,...
From August 1990. It was in the form of a note sent to all the people in the statistics group of Bell Labs, where I’d worked that summer. To all: Here’s the abstract of the work I’ve done this summer. It’s stored in the file, /fs5/gelman/abstract.bell, and copies of the Figures 1-3 are on Trevor’s
Milano R net, in collaboration with Quantide, organizes an "Introduction to R" course Milano; June 7-8, 2012 Continue reading →
In a previous post I used JAGS to build the Bayesian equivalent of a two-way ANOVA. Effects were determined of products, panelists and their interaction. In this post this model will be rebuild to provide a more simplified and advanced model. The inter...
We've been more sensitive to accounting for multiple comparisons recently, in part due to work that Nick and colleagues published on the topic. In this entry, we consider results from a randomized trial (Kypri et al., 2009) to reduce problem drinking ...
The latest local R user group to join the fold is the Köln R User Group, now the sixth R user group in Germany. Their first group meeting will be on July 6, with presentations on ANOVA, ggplot2 graphics in Deducer, and writing R code with Emacs's Org-mode. If you're in the Cologne area, this would be a great...
In this post it is examined if it is possible to use Bayesian methods and specifically JAGS to analyze sensory profiling data. The aim is not to obtain different results, but rather to confirm that the results are fairly similar. The data used is the c...
JGR LogoThis post introduces how to use the Java Gui for R (JGR, pronounced Jaguar) along with the Deducer package (manual here) to get a fairly full featured graphical user interface for R.InstallationNote: Be sure you are logged into an account with ...
While exploring the Julia manual recently, I realized that it might be helpful to put the basic vocabularies of Julia and R side-by-side for easy comparison. So I took Hadley Wickham’s R Vocabulary section from the book he’s putting together on the devtools wiki, put all of the functions Hadley listed into a CSV file,
This post describes the last puzzle piece of the model. The link of instrumental to sensory data. Together with the previous pieces this leads to a model starting from physico-chemical measurements, to sensory data, to consumers' perception and finally...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
