915 search results for "parallel"

Feature Selection Strikes Back (Part 1)

April 29, 2013
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Feature Selection Strikes Back (Part 1)

In the feature selection chapter, we describe several search procedures ("wrappers") that can be used to optimize the number of predictors. Some techniques were described in more detail than others. Although we do describe genetic algorithms and how they can be used for reducing the dimensions of the data, this is the first of series of blog posts that...

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A Brief Tour of the Trees and Forests

April 29, 2013
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A Brief Tour of the Trees and Forests

Tree methods such as CART (classification and regression trees) can be used as alternatives to logistic regression. It is a way that can be used to show the probability of being in any hierarchical group. The following is a compilation of many of the key R packages that cover trees and forests.  The goal here

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How UpStream uses R for Attribution Analysis

April 29, 2013
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Major retailers like Williams Sonoma use UpStream Software for marketing analytics, including revenue attribution, targeting, and optimization. In the video below Tess Nesbitt (senior statistician at UpStream) describes how she uses Revolution R Enterprise and Hadoop to figure out the impact on various marketing channels (for example direct mail, email offers, and catalogs) on consumer retail sales. (The slides...

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Using plyr and doMC for quick and easy apply-family functions

April 26, 2013
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Using plyr and doMC for quick and easy apply-family functions

A few weeks back I dedicated a short amount of time to actually read what plyr (Wickham, 2011) is about and I was surprised. The whole idea behind plyr is very simple: expand the apply() family to do things easy. plyr has...

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FasteR! HigheR! StrongeR! – A Guide to Speeding Up R Code for Busy People

April 25, 2013
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FasteR! HigheR! StrongeR! – A Guide to Speeding Up R Code for Busy People

This is an overview of tools for speeding up your R code that I wrote for the Davis R Users’ Group. First, Ask “Why?” It’s customary to quote Donald Knuth at this point, but instead I’ll quote my twitter buddy Ted Hart to illustrate a point: I’m just going to say it.I like for loops in #Rstats,...

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Announcing Revolution R Enterprise 6.2

April 24, 2013
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Announcing Revolution R Enterprise 6.2

We are pleased to announce that Revolution R Enterprise Release 6.2 is available to new subscribers today. This new software release from Revolution Analytics includes a number of key new features: Support for open source R 2.15.3, the latest stable release of R. Since Release 2.14.2, the R Project has added 89 new features, 11 performance enhancements and 139...

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Installation of WRS package (Wilcox’ Robust Statistics)

April 22, 2013
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Some users had trouble installing the WRS package from R-Forge. Here’s a method that should work automatically and fail-safe: ?View Code RSPLUS# first: install dependent packages install.packages(c("MASS", "akima", "robustbase"))   # second: install suggested packages install.packages(c("cobs", "robust", "mgcv", "scatterplot3d", "quantreg", "rrcov", "lars", "pwr", "trimcluster", "parallel", "mc2d", "psych", "Rfit"))   # third: install WRS install.packages("WRS", repos="http://R-Forge.R-project.org",

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Time Varying Higher Moments with the racd package.

April 22, 2013
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Time Varying Higher Moments with the racd package.

The Autoregressive Conditional Density (ACD) model of Hansen (1994) extended GARCH models to include time variation in the higher moment parameters. It was a somewhat natural extension to the premise of time variation in the conditional mean and variance, though it probably raised more questions than it, or subsequent research have been able to answer.

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Time Varying Higher Moments with the racd package.

April 22, 2013
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Time Varying Higher Moments with the racd package.

The Autoregressive Conditional Density (ACD) model of Hansen (1994) extended GARCH models to include time variation in the higher moment parameters. It was a somewhat natural extension to the premise of time variation in the conditional mean and variance, though it probably raised more questions than it, or subsequent research have been able to answer.

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Prioritizing project stakeholders using social network metrics

April 20, 2013
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Prioritizing project stakeholders using social network metrics

Identifying project stakeholders and their requirements is a very important factor in the success of any project. Existing techniques tend to be very ad-hoc. In her PhD thesis Soo Ling Lim came up with a very interesting solution using social network analysis and what is more made her raw data available for download I have

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