Based on last week's faster algorithm I wanted to finish with car weights. Unfortunately a fail again. By now it is a fail of myself, it needs a bit more dedication and grunt than I am willing and able to give for this blog. This week I added...

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Heatmaps are a great way to visualize data matrices. Heatmap color and organization can be used to encode information about the data and metadata to help learn about the data at hand. An example of this could be looking at the raw data or hierarchically clustering samples and variables based on their similarity or differences.

I have been having some issues generating spatial unions and intersections using the rgeos package. The package is extremely powerful, as it serves as an R interface to the powerful GEOS engine. However, when working with shapefiles or polygons, quite often you will come across a whole range of errors, typically around topology exceptions. These occur

ggmap is a new tool which enables such visualization by combining the spatial information of static maps from Google Maps, OpenStreetMap, Stamen Maps or CloudMade Maps with the layered grammar of graphics implementation of ggplot2The library is developped by David Kahle and Hadley Wickham and in the latest R/Journal (Volume 5/1, June 2013),...

For database marketing or direct marketing people, they are always concerned about two questions before they send out mails or make calls to their customers:- How can they segment the customers in the database to find out who are more likely to response to their mails or buy their products? Which type of customers they

I frequently use lattice and ggplot2 to create trellis/faceted graphics. But, I gave up using these packages in a recent application, where I had initially constructed a complex graphic using the base R plotting functions. When I later decided that I wanted a faceted version, there was a dilema: re-create the complex graphic using lattice

Last post on modelling survival data from Veterinary Epidemiologic Research: parametric analyses. The Cox proportional hazards model described in the last post make no assumption about the shape of the baseline hazard, which is an advantage if you have no idea about what that shape might be. With a parametric survival model, the survival time