Blog Archives

Evaluating Optimization Algorithms in MATLAB, Python, and R

June 18, 2013
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Evaluating Optimization Algorithms in MATLAB, Python, and R

As those of you who read my last post know, I’m at the NIMBioS-CAMBAM workshop on linking mathematical models to biological data here at UT Knoxville. Day 1 (today) was on parameter estimation and model identifiability. Specifically, we (quickly) covered … Continue reading →

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Eigen-analysis of Linear Model Behavior in R

May 7, 2013
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Eigen-analysis of Linear Model Behavior in R

This post is actually about replicating the figures in Otto and Day: A Biologist’s Guide to Mathematical Modeling in Ecology and Evolution. The figures I’m interested in for this post are Figures 9.1 and 9.2 in the chapter ‘General Solutions … Continue reading →

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Citation Patterns in Ecology

April 29, 2013
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Citation Patterns in Ecology

I’m always curious to see who is citing my one paper. Turns out I actually have two papers, and the most cited paper (with 19 citations, which sounds paltry but for me is quite exciting) is certainly not the one … Continue reading →

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Python Complements R’s Shortcomings

April 23, 2013
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Python Complements R’s Shortcomings

I’m a big fan of open-source software for research. For example, R-statistics, Qgis, and Grass GIS are awesome programs. R can do any statistical tests and numerical modeling you can imagine; if there’s not a built-in function you can write … Continue reading →

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Why Do the New Orleans Saints Lose? Data Visualization II

December 26, 2012
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Why Do the New Orleans Saints Lose? Data Visualization II

I’m going to continue with my ‘making data visually appealing to the masses’ kick. I happen to like graphics and graphing data. I also happen to like American football (For the record, however, I’m a soccer player first, a rugby … Continue reading →

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Making Data Visually Appealing

December 16, 2012
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Making Data Visually Appealing

I’ve recently been considering the graphical presentation of data. I get the feeling that we, ecologists/scientsits, could be better at data presentation. Graphs must be informative, but they don’t have to be ugly. I think that making visually appealing charts … Continue reading →

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R for Ecologists: Permutation Analysis – t-tests

October 24, 2012
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R for Ecologists: Permutation Analysis – t-tests

You’ve carefully designed your experiment, you’ve meticulously collected your data, and you have a hypothesis to test. Unfortunately, your data is typical of ecology data: small sample sizes, messy, and non-normal. Your ideal test, the t-test, won’t work because of the … Continue reading →

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Loading Packages and Functions Automatically in R

October 2, 2012
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Loading Packages and Functions Automatically in R

For a long time, I was wondering how to get R to automatically load packages I use every time I open the program. For example, for a variety of reasons, I use the ‘Cairo’ package to save all my figures as … Continue reading →

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R for Ecologists: Putting Together a Piecewise Regression

August 19, 2012
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R for Ecologists: Putting Together a Piecewise Regression

Piecewise regression comes about when you have ‘breakpoints’, where there are clearly two different linear relationships in the data with a sudden, sharp change in directionality. This crops up occasionally in ecology when dealing with, for example, species richness of understory plants … Continue reading →

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R for Ecologists: Simulating Species-Area Curves (linear vs. nonlinear regression)

August 7, 2012
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R for Ecologists: Simulating Species-Area Curves (linear vs. nonlinear regression)

This post is about basic model simulation so we can get a feel for how curves are supposed to look given certain processes assumed by the model. One of the most prevalent patterns in ecology is the species-area (SAR) curve, which … Continue reading →

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