888 search results for "how to import image file to R"

Anaerobic Stress in Seeds – A Chemical Similarity Network Story

December 31, 2012
By
Anaerobic Stress in Seeds – A Chemical Similarity Network Story

The chemical similarity network or CSN is a great tool for organizing biological data based on known biochemistry or chemical structural similarity. Here is an example CSN for visualizing metabolomic  changes (measured via GC/TOF) due to anaerobic stress in germinating seeds. In this network edges are formed for chemical similarity scores > 75. Node color describes

Read more »

Integration of R, RStudio and Hadoop in a VirtualBox Cloudera Demo VM on Mac OS X

December 29, 2012
By
Integration of R, RStudio and Hadoop in a VirtualBox Cloudera Demo VM on Mac OS X

MotivationI was inspired by Revolution's blog and step-by-step tutorial from Jeffrey Breen on the set up of a local virtual instance of Hadoop with R. However, this tutorial describes the implementation using VMware's application. One downside to using VMware is that it's not free. I know most of the people including me like to hear the words open-source and free,...

Read more »

Row-wise summary curves in faceted ggplot2 figures

December 29, 2012
By
Row-wise summary curves in faceted ggplot2 figures

I really enjoy reading the Junk Charts blog.  A recent post made me wonder how easy it would be to add summary curves for small-multiple type plots, assuming the “small multiples” to summarize were the X component of a ggplot2::facet_grid(Y ~ X) … Continue reading →

Read more »

UEFA, what were the odds ?

December 27, 2012
By
UEFA, what were the odds ?

Ok, I was supposed to take a break, but Frédéric, professor in Tours, came back to me this morning with a tickling question. He asked me what were the odds that the Champions League draw produces exactly the same pairings from the practice draw, and the official one (see e.g. dailymail.co.uk/…). To be honest, I don’t know much about soccer, so...

Read more »

My Intro to Multiple Classification with Random Forests, Conditional Inference Trees, and Linear Discriminant Analysis

December 27, 2012
By
My Intro to Multiple Classification with Random Forests, Conditional Inference Trees, and Linear Discriminant Analysis

After the work I did for my last post, I wanted to practice doing multiple classification.  I first thought of using the famous iris dataset, but felt that was a little boring.  Ideally, I wanted to look for a practice … Continue reading →

Read more »

Binary Classification – A Comparison of “Titanic” Proportions Between Logistic Regression, Random Forests, and Conditional Trees

December 23, 2012
By
Binary Classification – A Comparison of “Titanic” Proportions Between Logistic Regression, Random Forests, and Conditional Trees

Now that I’m on my winter break, I’ve been taking a little bit of time to read up on some modelling techniques that I’ve never used before. Two such techniques are Random Forests and Conditional Trees.  Since both can be used … Continue reading →

Read more »

A simple web application using Rook

December 21, 2012
By
A simple web application using Rook

by Ben Ogorek I'm grateful to Rook for helping me, a simple statistician, learn a few fundamentals of web technology. For R web application development, there are increasingly polished methods available (most notably Shiny ), but you can build one...

Read more »

Working with geographical Data. Part 1: Simple National Infomaps

December 21, 2012
By
Working with geographical Data. Part 1: Simple National Infomaps

There is a popular expression in my country called “Gastar polvora en chimangos”, whose translation in English would be “spending gunpowder in chimangos”. Chimango is a kind of bird whose meat is useless for humans. So “spending gunpowder in chimangos” … Continue reading →

Read more »

Generation of E-Learning Exams in R for Moodle, OLAT, etc.

December 20, 2012
By
Generation of E-Learning Exams in R for Moodle, OLAT, etc.

(Guest post by Achim Zeileis) Development of the R package exams for automatic generation of (statistical) exams in R started in 2006 and version 1 was published in JSS by Gr?n and Zeileis (2009). It was based on standalone Sweave exercises, that can be combined …Read more »

Read more »

Generalized Boosted Regression with A Monotonic Marginal Effect for Each Predictor

December 18, 2012
By
Generalized Boosted Regression with A Monotonic Marginal Effect for Each Predictor

In the practice of risk modeling, it is sometimes mandatory to maintain a monotonic relationship between the response and each predictor. Below is a demonstration showing how to develop a generalized boosted regression with a monotonic marginal effect for each predictor. Plot of Variable Importance Plot of Monotonic Marginal Effects

Read more »