Monthly Archives: September 2012

ROracle support for TimesTen In-Memory Database

September 27, 2012
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Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in ve...

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Using R in Political Controversies: Unemployment Reduction Prowess Under Bush versus Obama Years

September 27, 2012
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Using R in Political Controversies: Unemployment Reduction Prowess Under Bush versus Obama Years

Editor’s note: R-bloggers does not take a political side. Since this is an important topic, this post has the comments turned on. Also, If you wish to write a reply post (which includes an R context), you are welcome to contact me to have it published. This post was written by Prof. H. D. Vinod. Fordham University, New York.

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Continuous dispersal on a discrete lattice

September 27, 2012
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Continuous dispersal on a discrete lattice

Dispersal is a key process in many domains, and particularly in ecology. Individuals move in space, and this movement can be modelled as a random process following some kernel. The dispersal kernel is simply a probability distribution describing the distance travelled in a given time frame. Since space is continuous, it is natural to use

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Bounding sums of random variables, part 1

September 27, 2012
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Bounding sums of random variables, part 1

For the last course MAT8886 of this (long) winter session, on copulas (and extremes), we will discuss risk aggregation. The course will be mainly on the problem of bounding  the distribution (or some risk measure, say the Value-at-Risk) for two random variables with given marginal distribution. For instance, we have two Gaussian risks. What could be be worst-case scenario...

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Simplest possible heatmap with ggplot2

September 27, 2012
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Simplest possible heatmap with ggplot2

Featuring the lovely “spectral” palette from Colorbrewer. This really just serves as a reminder of how to do four things I frequently want to do: Make a heatmap of some kind of matrix, often a square correlation matrix Reorder a factor vari...

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Calling Minimum Correlation Algorithm from Excel using RExcel & VBA

September 26, 2012
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Calling Minimum Correlation Algorithm from Excel using RExcel & VBA

I want to show the example of calling the Minimum Correlation Algorithm from Excel. I will use RExcel to connect R and Excel and will create a small VBA cell array function to communicate between Excel and R. I have previously discussed the concept of connecting R and Excel in the “Calling Systematic Investor Toolbox

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eeptools 0.1 Available on CRAN Now!

September 26, 2012
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eeptools 0.1 is available now on CRAN! You can install it by simply typing:install.packages('eeptools')in your R console now. The package allows users to play with a number of built in datasets for folks in education beginning to learn R, custom themes...

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structure and uncertainty, Bristol, Sept. 26

September 26, 2012
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structure and uncertainty, Bristol, Sept. 26

Another day full of interesting and challenging—in the sense they generated new questions for me—talks at the SuSTain workshop. After another (dry and fast) run around the Downs; Leo Held started the talks with one of my favourite topics, namely the theory of g-priors in generalized linear models. He did bring a new perspective on

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Association Rule Learning and the Apriori Algorithm

September 26, 2012
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Association Rule Learning and the Apriori Algorithm

Association Rule Learning (also called Association Rule Mining) is a common technique used to find associations between many variables. It is often used by grocery stores, retailers, and anyone with a large transactional databases. It’s the same way that Target knows your pregnant or when you’re buying an item on Amazon.com they know what else you want

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Merging Data Sets Based on Partially Matched Data Elements

September 26, 2012
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Merging Data Sets Based on Partially Matched Data Elements

A tweet from @coneee yesterday about merging two datasets using columns of data that don’t quite match got me wondering about a possible R recipe for handling partial matching. The data in question related to country names in a datafile that needed fusing with country names in a listing of ISO country codes. The original

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