2224 search results for "twitteR"

Music file graphs with R

May 22, 2011
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Music file graphs with R

Today we will use R to extract some interesting summary statistics regarding the music files stored in the computer. For all mp3 files I keep certain metadata in their ID3 tag. We will use this information to explore the distribution of music files with respect to the year of release. All the following are done

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Terry’s spiel

May 22, 2011
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Terry’s spiel

“We don’t need likelihood functions; we just need to know how to simulate from (…) We don’t need models with sufficient statistics; we just need summary statistics (…) We don’t need to be Bayesian; we just need to be approximately so. We don’t need theory to tell us our method works; we just need

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Smaller or greater? – episode II

May 20, 2011
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Smaller or greater? – episode II

In a previous post I introduced the following game: Suppose you play the following game: Someone holds a set of cards with the numbers {1,2,…,N} in random order, opens up the first card and asks if the next card is greater or smaller. Every time you predict correctly, you get one point, while every wrong

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Great circles, raster, sp and lattice

Great circles, raster, sp and lattice

Recently I found a post at FlowingData with a detailed tutorial to map connections with great circles with R. The tutorial of FlowingData is excellent, but I feel more comfortable with the sp classes and methods, and with the lattice and latticeExtra packages. Besides, I want to use the free spatial data available from the

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Syntax highlighting of R code at WordPress.com

May 20, 2011
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Syntax highlighting of R code at WordPress.com

If your WordPress blog is hosted at WordPress.com (like this one), you may know that source code in posts is formatted and highlighted using a shortcode, as explained here. Until recently, R was not on the list of supported languages (neither was Perl), but I noticed today that both of them are now supported. This

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Friday fun with: Google Trends

May 19, 2011
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Friday fun with: Google Trends

Some years ago, Google discovered that when people are concerned about influenza, they search for flu-related information and that to some extent, search traffic is an indicator of flu activity. Google Flu Trends was born. Illness is sweeping through our department this week and I have succumbed. It’s not flu but at one point, I

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Stata-like Marginal Effects for Logit and Probit Models in R [2]

May 18, 2011
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Stata-like Marginal Effects for Logit and Probit Models in R [2]

My thanks to those who emailed comments and suggestions for my ‘mfx’ function, I’m happy that I could fill a void for some people. I also received a request/suggestion from Tony Cookson, along with a helpful fix for a bug in the code, to include an option that would allow the user to specify values

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Stata-like Marginal Effects for Logit and Probit Models in R

May 17, 2011
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Stata-like Marginal Effects for Logit and Probit Models in R

Although this blog’s primary focus is time series, one feature I missed from Stata was the simple marginal effects command, ‘mfx compute’, for cross-sectional work, and I could not find an adequate replacement in R. To bridge this gap, I’ve written a (rather messy) R function to produce marginal effects readout for logit and probit

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A survey of the [60′s] Monte Carlo methods [2]

May 17, 2011
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A survey of the [60′s] Monte Carlo methods [2]

The 24 questions asked by John Halton in the conclusion of his 1970 survey are Can we obtain a theory of convergence for random variables taking values in Fréchet spaces? Can the study of Monte Carlo estimates in separable Fréchet spaces give a theory of global approximation? When sampling functions, what constitutes a representative sample

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How to do a quantitative literature review in R

May 17, 2011
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How to do a quantitative literature review in R

In the early stages of a literature review, you may have hundreds of papers and not know how to even begin sorting through them. In this post, I show you how to perform a two-stage clustering analysis with R so that you can identify the main groups within your data, based on key attributes of each paper.

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