1542 search results for "regression"

Tibshirani’s original paper on the lasso. Breiman’s…

December 6, 2012
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Tibshirani’s original paper on the lasso.
Breiman’s…

Tibshirani’s original paper on the lasso. Breiman’s Garotte — 1993 Tibshirani lasso paper submitted — 1994 Tibshirani lasso paper revised — 1995 Tibshirani lasso paper accepted — 1996 This is one of those papers that I’m so excited about, I feel like “You should just read the whole thing! It’s all good!” But I realise that’s less than reasonable. Here is a bit of summary,...

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How a Mexican state ended up with more drug war homicides than total homicides

December 5, 2012
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How a Mexican state ended up with more drug war homicides than total homicides

During 2007 and 2008 the Mexican state of Sinaloa had more drug war-related homicides than total homicides. This should in theory be impossible since drug war homicides are a subset of total homicides. How did this happen? Here is a chart from my old post highlighting the monthly difference between the...

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Modis QC Bits

December 5, 2012
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Modis QC Bits

In the course of working through my MODIS  LST project and reviewing the steps that Imhoff and Zhang took as well has the data preparations other researchers have taken ( Neteler ) the issue of MODIS Quality control bits came up.  Every MODIS  HDF file comes with multiple SDS or multiple layers of data. For

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Climate: Misspecified

December 4, 2012
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Climate: Misspecified

I'm usually quite a big fan of the content syndicated on R-Bloggers (as this post is), but I came across a post yesterday that was as statistically misguided as it was provocative. In this post, entitled "The Surprisingly Weak Case for Global Warming," the author (Matt Asher) claims that the trend toward hotter average global temperatures over the last

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The surprisingly weak case for global warming

December 3, 2012
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The surprisingly weak case for global warming

I welcome your thoughts on this post, but please read through to the end before commenting. Also, you’ll find the related code (in R) at the end. For those new to this blog, you may be taken aback (though hopefully not bored or shocked!) by how I expose my full process and reasoning. This is

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Trading with Support Vector Machines (SVM)

November 30, 2012
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Trading with Support Vector Machines (SVM)

Finally all the stars have aligned and I can confidently devote some time for back-testing of new trading systems, and Support Vector Machines (SVM) are the new “toy” which is going to keep me busy for a while. SVMs are a well-known tool from the area of supervised Machine Learning, and they are used both

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Another Way to Access R from Python – PypeR

November 29, 2012
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Another Way to Access R from Python – PypeR

Different from RPy2, PypeR provides another simple way to access R from Python through pipes (http://www.jstatsoft.org/v35/c02/paper). This handy feature enables data analysts to do the data munging with python and the statistical analysis with R by passing objects interactively between two computing systems. Below is a simple demonstration on how to call R within Python

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bigglm on your big data set in open source R, it just works – similar as in SAS

bigglm on your big data set in open source R, it just works – similar as in SAS

In a recent post by Revolution Analytics (link & link) in which Revolution was benchmarking their closed source generalized linear model approach with SAS, Hadoop and open source R, they seemed to be pointing out that there is no 'easy' R open source solution which exists for building a poisson regression model on large datasets.    This post is about...

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OpenScoring: Open Source Scoring of PMML Models via REST

November 27, 2012
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OpenScoring: Open Source Scoring of PMML Models via REST

The other day I stumbled accross an amazing PMML model API called jpmml.  It's written in Java and supports PMML 4.1 (and older).  Neural networks, random forests, regression and trees PMML models can be consumed and used for scoring.I decide...

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Minimizing Bias in Observational Studies

November 26, 2012
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Minimizing Bias in Observational Studies

Measuring the effect of a binary treatment on a measured outcome is one of the most common tasks in applied statistics. Examples of these applications abound, like the effect of smoking on health, or the effect of low birth weight on cognitive development. In an ideal world we would like to be able to assign

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