In case you missed them, here are some articles from September of particular interest to R users. You can now browse the R-devel sources and changelogs at GitHub. R is used to create a 3-D animation of the Antarctic ice cap. At the DataWeek SF conference, R users from eBay, Intuit, Minted and other companies describe how R is...
Monthly Archives: October 2012
Another R + iButton script
Previously I’ve detailed R scripts that automate the launching and downloading Maxim iButton thermochron data loggers. I’m typically doing the launching and downloading at separate times in my workflow, since I have duplicate iButtons to swap out, so separate scripts work for me. Ryan Knowles recently contributed a combined version of these scripts that downloads
Product revenue prediction with R – part 2
After development of predictive model for transactional product revenue -(Product revenue prediction with R – part 1), we can further improvise the model prediction by modifications in the model. In this post, we will see what are the steps required for model improvement. With the help of a set of model summary parameters, the data
Product revenue prediction with R – part 3
After development and improvement of predictive model with R (as in the previous blog), I have focused here about making a prediction with the R model ( linear regression model ) and comparison with the Google prediction API model. In statistical modeling, R will calculate intercept and variable coefficients to describe the relationship between a
Product revenue prediction with R – part 1
In my upcoming three blogs, I am going to discuss about how Product managers, Data analyst and Data scientists can develop model for the prediction of the transactional product revenue on the basis of user actions like total numbers of time product added to the cart, total numbers of time product added to the cart,
Summarizing Data
In this post, I'll go over four functions that you can use to nicely summarize your data. Before any regression analysis, a descriptive analysis is key to understanding your variables and the relationships between them. Next week, I'll have...
Example 10.5: Convert a character-valued categorical variable to numeric
In some settings it may be necessary to recode a categorical variable with character values into a variable with numeric values. For example, the matching macro we discussed in example 7.35 will only match on numeric variables. One way to conve...
DIY ZeroAccess GeoIP Analysis : So What?
NOTE: A great deal of this post comes from @jayjacobs as he took a conversation we were having about thoughts on ways to look at the data and just ran like the Flash with it. Did you know that – if you’re a US citizen – you have approximately a 1 in 5 chance of getting the
Simulating Spatial Data
# Spatial data tags are an increasingly recorded for data that is being generating as a result of widescale implementation of GPS technology.# In this post I will present a simulation in which the population is distributed around a single town center.#...
CrowdANALYTIX – Ideation Contest – Warranty Pricing
I recently completed an ideation contest on CrowdANALYTIX where the participants had to build an approach towards warranty pricing and fraud detection.Ideation contests are quite different from the usual data mining contests where the objective is...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
