# Monthly Archives: June 2013

## Exploratory Data Analysis – Kernel Density Estimation and Rug Plots on Ozone Data in New York and Ozonopolis

For the sake of brevity, this post has been created from the second half of a previous long post on kernel density estimation.  This second half focuses on constructing kernel density plots and rug plots in R.  The first half focused on the conceptual foundations of kernel density estimation. Introduction This post follows the recent

## Using R to Produce Scalable Vector Graphics for the Web

June 30, 2013
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Statistical software is normally used during the analysis stage of a project and a cleaned up static graphic is created for the presentation.  If the presentation is in web format then there are some considerations that are needed. The trick is to find ways to implement those graphs in that web format so the graph

## How pqR makes programs faster by not doing things

June 30, 2013
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One way my faster version of R, called pqR (see updated release of 2013-06-28), can speed up R programs is by not even doing some operations. This happens in statements like for (i in 1:1000000) ..., in subscripting expressions like v, and in logical expressions like any(v>0) or all(is.na(X)). This is done using pqR’s internal “variant result” mechanism, which is

## Subscribing to updates from R-bloggers.com

June 30, 2013
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Tomorrow (July 1, 2013), Google Reader will retire. I can imagine the shock this will be for the 5,821 followers of this site who uses Google Reader in order to followup on news and tutorials from the global R world. If you are have considering a more committed relationship with this site and didn’t know what to do –...

## Faster calculation

June 30, 2013
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Last week I decided to speed up my distribution fitting functions of two weeks ago. These were bold words. My try of Rcpp was a failure. Just plain optimization helped a bit better. Using the compiler package added a bit. (the compiler package does not...

## Learning R: Parameter Fitting for Models Involving Differential Equations

June 30, 2013
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$Learning R: Parameter Fitting for Models Involving Differential Equations$

It looks like MATLAB, Octave and Python seem to be the preferred tools for scientific and engineering analysis (especially those involving physical models with differential equations). However as part of my learning R experience, I wanted to check out some … Continue reading →

## An .EPS to .PDF converter (using LaTeX!)

June 30, 2013
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I am about to go on a short holiday, so I was tidying the code lines I had scattered around before leaving… And I found this: a minimal EPS to PDF converter, which is barely a LaTeX template. It is … Sigue leyendo →

## R to GeoJSON

June 30, 2013
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UPDATE As you can see in Patrick's comment below you can convert to GeoJSON format files with rgdal as an alternative to calling the Ogre web API described below. See here for example code for converting to GeoJSON with rgdal. GitHub recently introduced the ability to render GeoJSON files on their site as maps here, and recently...

## R to GeoJSON

June 30, 2013
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GitHub recently introduced the ability to render GeoJSON files on their site as maps here, and recently introduced here support for TopoJSON, an extension of GeoJSON can be up to 80% smaller than GeoJSON, support for other file extensions (.topojson and .json), and you can embed the maps on other sites (so awesome). The underlying...