Monthly Archives: March 2013

AQP News and Updates

March 12, 2013
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The AQP family of R packages has seen a lot of development over the last 3 months. Some of the highlights include: HTML manual pages with syntax-highlighting and figures, c/o knitr new vignettes: "dealing with bad data", gridded SSURGO (gSSURGO) demo,...

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Job advert

March 12, 2013
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Job advert

We finally got around to prepare everything we needed to advertise the position which will be available in the MRC grant we've been awarded last year.The project will run for 30 months and we're looking for a post-doctoral candidate to work on the Rese...

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reports 0.1.2 Released

March 12, 2013
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reports 0.1.2 Released

I’m very pleased to announce the release of reports : An R package to assist in the workflow of writing academic articles and other reports. This is the first CRAN release of reports: http://cran.r-project.org/web/packages/reports/index.html The reports package assists in writing … Continue reading →

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Third Milano R net meeting to be held on April 18, 2013

March 12, 2013
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Third Milano R net meeting April 18, 2013 @ 6.00 PM Fiori Oscuri Bistrot & Bar Via Fiori Oscuri, 3 Milano Further details will be published shortly. Stay connected!

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How to use optim in R

March 12, 2013
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How to use optim in R

A friend of mine asked me the other day how she could use the function optim in R to fit data. Of course there are functions for fitting data in R and I wrote about this earlier. However, she wanted to understand how to do this from scratch using optim. The function optim provides algorithms for general...

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Generating a multivariate gaussian distribution using RcppArmadillo

March 12, 2013
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Generating a multivariate gaussian distribution using RcppArmadillo

There are many ways to simulate a multivariate gaussian distribution assuming that you can simulate from independent univariate normal distributions. One of the most popular method is based on the Cholesky decomposition. Let’s see how Rcpp and Armadillo perform on this task. #include <RcppArmadillo.h> // ] using namespace Rcpp; // ] arma::mat mvrnormArma(int n, arma::vec mu, arma::mat sigma) { int ncols...

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Generating a multivariate gaussian distribution using RcppArmadillo

March 12, 2013
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Generating a multivariate gaussian distribution using RcppArmadillo

There are many ways to simulate a multivariate gaussian distribution assuming that you can simulate from independent univariate normal distributions. One of the most popular method is based on the Cholesky decomposition. Let’s see how Rcpp and Armadillo perform on this task. #include <RcppArmadillo.h> // ] using namespace Rcpp; // ] arma::mat mvrnormArma(int n, arma::vec mu, arma::mat sigma) { int ncols...

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High Resolution Figures in R

March 12, 2013
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High Resolution Figures in R

As I was recently preparing a manuscript for PLOS ONE, I realized the default resolution of R and RStudio images are insufficient for publication. PLOS ONE requires 300 ppi images in TIFF or EPS (encapsulated postscript) format. In R plots … Continue reading →

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R 101

March 11, 2013
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as.character() is your friendas.character() is your friend Sometimes when you open a data file (lets say a .csv), variables will be recognized as factor whereas it should be numeric. It is therefore tempting to simply convert the variable to numeric using as.numeric(). Big mistake! If...

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Simulating Random Multivariate Correlated Data (Categorical Variables)

March 11, 2013
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Simulating Random Multivariate Correlated Data (Categorical Variables)

This is a repost of the second part of an example that I posted last year but at the time I only had the PDF document (written in ). This is the second example to generate multivariate random associated data. This example shows how to generate ordinal, categorical, data. It is a little more complex than generating continuous

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