We'll get back to code examples later this week, but wanted to let you know about an R package with updated functionality in the meantime.The appropriate analysis of sample surveys requires incorporation of complex design features, including stratification, clustering, weights, and finite population correction. These can be address in SAS and R for many common models. Section...
Posts Tagged ‘ Clustering ’
Data Visualization and R Programming Books (Updated)
Download "Getting Started with the Social Media Analytics Research Toolkit" (pdf, 1.25 megabytes) Download the Social Media Analytics Research Toolkit Download Code Like A Pirate - The #rstats Appliance from the SUSE Gallery Disclosure As you probably ...
Machine Learning in R
Revolutions blog recently posted a link to R code by Joshua Reich with self-contained examples of using machine learning techniques in R, including various clustering methods (k-means, nearest neighbor, and kernel), recursive partitioning (CART), principle components analysis, linear discriminant analysis, and support vector machines. This post also links to some slides that go over the basics
Hierarchical Clustering in R
Hierarchical clustering is a technique for grouping samples/data points into categories and subcategories based on a similarity measure. Being the powerful statistical package it is, R has several routines for doing hierarchical clustering. The basic command for doing HC is hclust(d, method = "complete", members=NULL) Nearly all clustering approaches use a concept of distance. Data points
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
