Monthly Archives: November 2012

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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Because it’s Friday: Evolution of a research paper about Reddit

November 30, 2012
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Computer Science PhD student Tim Weninger wrote a 10-page paper for the World Wide Web conference looking at how Reddit users interact on the discussion pages of the social news site. During the process, he saved 463 revisions of the paper in a source-code control system. Then, he wrote a computer program to animate each revision of the paper....

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Real-Time Predictive Analytics with Big Data, and R

November 30, 2012
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Real-Time Predictive Analytics with Big Data, and R

Can R be used for real-time applications? Absolutely! The key is in setting up an technology stack that can support real-time interactions with models developed in R ... and a clear understanding of what "real-time" really means, and its implications in the context of Big Data. I explained how this works in yesterday's webinar, Real-Time Predictive Analytics with Big...

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Lauren Yamane on Matrix Population Models in R

November 30, 2012
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Lauren Yamane on Matrix Population Models in R

Last week in Davis R Users’ Group, Lauren Yamane showed us how she created and analyzed a stochastic age-structured population in R. Her examples are below. Her original scripts can be found as *.Rmd files here A note to UC Davis students: This topic and others will be covered by Marissa Baskett and Sebastian Schreiber in...

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Data types part 4: Logical class

November 30, 2012
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Data types part 4: Logical class

First, an update:  A commentator has asked me to post my code so that it is easier to practice the examples I show here.  It will take me a little bit of time to get all of my code for past posts well-documented and readable, but I have uploa...

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Finding a bright object

November 30, 2012
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Finding a bright object

Finally, to return to the challenge I laid out in the first of this series on image manipulation in R: can we do anything as cool in R as can be done in Mathematica? Like, for example, this illustration of how to search images of the surface of Mars...

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edply: combining plyr and expand.grid

November 30, 2012
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edply: combining plyr and expand.grid

Here’s a code snippet I thought I’d share. Very often I find myself checking the output of a function f(a,b) for a lot of different values of a and b, which I then need to plot somehow. An example: here’s a function that computes the value of a sinusoidal function on a grid of points,

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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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Earthquakes Over the Past 7 Days

November 29, 2012
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Earthquakes Over the Past 7 Days

This is a brief example using the maps in R and to highlight a source of data.  This is real-time data and it comes from the U.S. Geological Society.  This shows the location of earthquakes with magnitude of at least 1.0 in the lower 48 states. library(maps) library(maptools) library(rgdal) eq = read.table(file="http://earthquake.usgs.gov/earthquakes/catalogs/eqs7day-M1.txt", fill=TRUE, sep=",", header=T) plot.new()

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2012-11 Generating Animation Sequence Descriptions

November 29, 2012
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This report describes the animaker package for generating descriptions of animation sequences. An animation sequence is composed by combining atomic animations in series to create sequence animations or in parallel to create track animations. Functions are provided for manipulating animation … Continue reading →

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