789 search results for "maps"

Health Care Costs – Part 3, "Why You Are Paying More"

July 19, 2012
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Health Care Costs – Part 3, "Why You Are Paying More"

Malpractice - A Booming Industry? Perhaps authors Frank Sloan, Randall Bovbjerg and Penny Githens capture it best from their book Insuring Medical Malpractice: "If aging Doctor Kildare were to return to medical practice today, having been...

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Mapping Public Opinion: A Tutorial

July 18, 2012
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Mapping Public Opinion: A Tutorial

At the upcoming 2012 summer meeting of the Society of Political Methodology, I will be presenting a poster on Isarithmic Maps of Public Opinion. Since last posting on the topic, I have made major improvements to the code and robustness of the modeling approach, and written a tutorial that illustrates the production of such maps. This … Continue reading →

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Project Euler — problem 14

July 16, 2012
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Project Euler — problem 14

It’s Monday today! It’s work day! And I’ve already worked on computer for two hours. Time for a break, which is the 14th problem of Project Euler. The following iterative sequence is defined for the set of positive integers: n n/2 (n … Continue reading →

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Map biodiversity records with rgbif and dismo packages in R

July 15, 2012
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Map biodiversity records with rgbif and dismo packages in R

In the earlier post we generated maps from GBIF biodiversity records using maps and ggplot2 packages. We used world map with country borders for that. Now we will generate maps with google maps as base layer using dismo package. Like earlier we download data for Danaus chrysippus from GBIF using occurrencelist function into a data

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Map biodiversity records with rgbif and dismo packages in R

July 15, 2012
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Map biodiversity records with rgbif and dismo packages in R

In the earlier post we generated maps from GBIF biodiversity records using maps and ggplot2 packages. We used world map with country borders for that. Now we will generate maps with google maps as base layer using dismo package. Like earlier we download data for Danaus chrysippus from GBIF using occurrencelist function into a data

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Dynamical systems: Mapping chaos with R

July 13, 2012
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Dynamical systems: Mapping chaos with R

Chaos. Hectic, seemingly unpredictable, complex dynamics. In a word: fun. I usually stick to the warm and fuzzy world of stochasticity and probability distributions, but this post will be (almost) entirely devoid of randomness. While chaotic dynamics are entirely deterministic, their sensitivity to initial conditions can trick the observer into seeing iid. In ecology, chaotic

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Napa Valley wine tasting map: interactive version

July 12, 2012
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Napa Valley wine tasting map: interactive version

Got some great reactions to the Napa Valley wine tasting map made with the ggmap package I posted on Monday. A couple of people asked if similar maps could be made for other wine regions (like Australia's Hunter Valley, or the Walla Walla region in Washington): provided you have a list of winery addresses, tweaks to the same R...

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Health Care Costs – Part 2, "Unhealthy Things Not Related to the Problem"

July 11, 2012
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Health Care Costs – Part 2, "Unhealthy Things Not Related to the Problem"

Lighting Up Way back in the day, folks believed that smoking was not only cool but also completely safe. As Marcel Danesi states in his book Of Cigarettes, High Heels, and Other Interesting Things, Second Edition: An Introduction to Semiotics ...

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A Napa Valley wine tasting map, made with R and ggmap

July 9, 2012
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A Napa Valley wine tasting map, made with R and ggmap

R has had a maps package available since the very early days. It's great for simple geographic maps, but the political boundaries can be out of date. For more detailed maps, you can also download shape files and use the sp package to draw borders directly. But for accurate and attractive maps of countries, roads and satellite imagery, nothing...

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Interest Differencing: Folk Commonly Followed by Tweeting MPs of Different Parties

July 6, 2012
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Interest Differencing: Folk Commonly Followed by Tweeting MPs of Different Parties

Earlier this year I doodled a recipe for comparing the folk commonly followed by users of a couple of BBC programme hashtags (Social Media Interest Maps of Newsnight and BBCQT Twitterers). Prompted in part by a tweet from Michael Smethurst/@fantasticlife about generating an ESP map for UK politicians (something I’ve also doodled before – Sketching

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