2539 search results for "map"

Revolution Newsletter: May 2013

May 17, 2013
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The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full May edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Gaming Analytics FTW! Join us on 13Jun13 at 10:00 AM PDT for our webinar...

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Strategic Zombie Simulation – Animation

May 17, 2013
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Strategic Zombie Simulation – Animation

# Escape Zombie Land! # This is a simulation an escape from a hot zombie zone. It freezes and gives an error if you get get killed so you had best not. You attempt to navigate the zone by constructing waypoints. # This is not a very clean s...

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Analyze More, Program Less: A Webinar about Using SciDB for Computational Finance

May 16, 2013
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Paradigm4 presents a webinar about using SciDB for scalable financial analytics. You’ll see how SciDB reaches Big Data scale without forcing you to become a computer scientist—no mapping, no reducing, no concocting parallel algorithms by hand. The webinar will also demonstrate SciDB-R, an R package that lets you remain an R programmer while enjoying the scalable

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Social Network Analysis at New Frontiers in Computing 2013

May 16, 2013
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Social Network Analysis at New Frontiers in Computing 2013

by Joseph Rickert This past Saturday, the New Frontiers in Computing Conference (NFIC 2013), held at Stanford University, explored the theme: Social Network Analysis: It’s Who You Know. The speakers were a well-chosen, eclectic lot who covered a remarkable array of issues in less than a full day. Ian Hersey, former CTO of Attensity spoke on Lessons from Large-Scale...

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Integration take two – Shiny application

May 13, 2013
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Integration take two – Shiny application

My last post discussed a technique for integrating functions in R using a Monte Carlo or randomization approach. The mc.int function (available here) estimated the area underneath a curve by multiplying the proportion of random points below the curve by the total area covered by points within the interval: The estimated integration (bottom plot) is

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Combining dataframes when the columns don’t match

May 13, 2013
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Combining dataframes when the columns don’t match

Most of my work recently has involved downloading large datasets of species occurrences from online databases and attempting to smoodge1 them together to create distribution maps for parts of Australia. Online databases typically have a ridiculous number of columns with … Continue reading →

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Who Has the Best Fantasy Football Projections: ESPN, CBS, NFL.com, or FantasyPros?

May 12, 2013
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Who Has the Best Fantasy Football Projections: ESPN, CBS, NFL.com, or FantasyPros?

In prior posts, I demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com.  In my last post, I demonstrated how to download FantasyPros projections, which aggregate projections from many different sources to increase prediction accuracy.  In this post, I will compare fantasy football projections from ESPN, CBS, NFL, and FantasyPros, including our average...

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The Guerilla Guide to R

May 12, 2013
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Update: Okay. I've uploaded a new template and things seem to be fine now. Update: I am aware the table of contents is not being displayed in bullet form as I intended. The web template I'm using seems to be buggy. It also seems to think this page is in Indonesian...Working on it! Table of Contents: Reading/Writing Files

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Playing cards, with R

May 11, 2013
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Playing cards, with R

In my courses on R, I usually show how to insert a picture as a background for a graph. But it is also to see the picture as an object, and to insert it in a graph everywhere we like to see it, as explained on the awesome blog http://rsnippets.blogspot.ca/…. (in a post published in January 2012). I wanted...

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Omni test for statistical significance

May 9, 2013
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Omni test for statistical significance

In survey research, our datasets nearly always comprise variables with mixed measurement levels – in particular, nominal, ordinal and continuous, or in R-speak, unordered factors, ordered factors and numeric variables. Sometimes it is useful to be able to do blanket tests of one set of variables (possibly of mixed level) against another without having to

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