2730 search results for "GIS"

It Takes 2 Lines of R Code to Discover Interesting Biology

October 23, 2012
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It Takes 2 Lines of R Code to Discover Interesting Biology

The following biological phenomenon demonstrates just how elegant R code can be. In vertebrate genomes, a methyl group (-CH3) can be added to nucleotides. Such process of methylation is commonly associated with gene suppression. Most of the cytosines in the … Continue reading →

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googleVis 0.3.0/0.3.1 is released: It’s faster!

October 23, 2012
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googleVis 0.3.0/0.3.1 is released: It’s faster!

Version 0.3.0 of the googleVis package for R has been released on CRAN on 20 October 2012. With this version we have been able to speed up the code considerably. The transformation of R data frames into JSON works significantly faster. The execution of the gvisMotionChart function in the World Bank demo is over 35 times...

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Is it meaningful to talk about a probability of “65.7%” that Obama will win the election?

October 22, 2012
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Is it meaningful to talk about a probability of “65.7%” that Obama will win the election?

The other day we had a fun little discussion in the comments section of the sister blog about the appropriateness of stating forecast probabilities to the nearest tenth of a percentage point. It started when Josh Tucker posted this graph from Nate Silver: My first reaction was: this looks pretty but it’s hyper-precise. I’m a The post Is...

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Predict User’s Return Visit within a day part-3

October 22, 2012
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Predict User’s Return Visit within a day part-3

Welcome to the last part of the series on predicting user’s revisit to the website. In the  first part of series, I generated the logistic regression model for prediction problem whether a user will come back on  website in next 24 hours. In the second part, I discussed about model improvement and seen the model accuracy.

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Distribution of colors by flag

October 22, 2012
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Distribution of colors by flag

A story: We showed you how to use R to assess flag similarity and make a scatter plot of raster images. Dr. Wickham referred us to the set of 2400 flag icons made available by GoSquared, and then (probably jokingly) challenged us to replicate the cool...

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Predict User’s Return Visit within a day part-2

October 22, 2012
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Predict User’s Return Visit within a day part-2

Welcome to the second part of the series on predicting user’s revisit to the website. In my earlier blog Logistic Regression with R, I discussed what is logistic regression. In the first part of the series, we applied logistic regression to available data set. The problem statement there was whether a user will return in

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Predict User’s Return Visit within a day part-1

October 22, 2012
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Predict User’s Return Visit within a day part-1

In my earlier blog, I have discussed about what is logistic regression? And how logistic model is generated in R? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict whether a user will return on website in next 24 hours. This

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Carl Morris Symposium on Large-Scale Data Inference (2/3)

October 20, 2012
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Carl Morris Symposium on Large-Scale Data Inference (2/3)

Continuing the summary of last week’s symposium on statistics and data visualization (see part 1 and part 3)… Here I describe Dianne Cook’s discussion of visual inference, and Rob Kass’ talk on statistics in cognitive neuroscience. [Edit: I've added a few … Continue reading →

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Introduction to Bayesian lecture: Accompanying handouts and demos

October 19, 2012
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Introduction to Bayesian lecture: Accompanying handouts and demos

I recently posted the slides from a guest lecture that I gave on Bayesian methods for biologists/ecologist. In an effort to promote active learning, the class was not a straight forward lecture, but rather a combination of informational input from me and opportunities for students to engage with the concepts via activities and discussion of

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Stella Copeland’s Intro to Mixed Models in R

October 19, 2012
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In D-RUG today, Stella Copeland gave a quick introduction to mixed models in R. Here’s the script that she presented: Get the data file for this script here Stella also recommends this paper by Ben Bolker as a quick introduction to the topic.

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