I’m announcing the alpha launch of EcoPy: Ecological Data Analysis in Python. EcoPy is a Python module that contains a number of  techniques (PCA, CA, CCorA, nMDS, MDS, RDA, etc.) for exploring complex multivariate data. For those of you familiar … Continue reading → [Read more...]

One of the reasons I switched to Python from R is because Python’s phylogenetic capabilities are very well developed, but R is catching up. I’m moving into phylogenetic community ecology, which requires a lot of tree manipulation and calculation of … Continue reading → [Read more...]

Python has some pretty awesome data-manipulation and graphing capabilities. If you’re a heavy R-user who dabbles in Python like me, you might wonder what the equivalent commands are in Python for dataframe manipulation. Additionally, I was curious to see how … Continue reading → [Read more...]

I have been working with Python recently and I have to say, I love it. There’s a learning curve, of course, which has been frustrating. However, once I got comfortable with it (and continue to do so), I found that … Continue reading → [Read more...]

My friends and co-workers got lucky enough to spend about two weeks living in the Aquarius habitat, NOAA’s undersea research lab in the Florida Keys. I, unfortunately, am stuck on dry land (or on a boat above the habitat, watching … Continue reading → [Read more...]

I’ve been reading about RLQ analysis, also known as the fourth corner method, for analyzing relationships between environmental characteristics and species traits. I was interested because I thought I might be using RLQ analysis to answer a specific set of … Continue reading → [Read more...]

I’ve written a few previous posts comparing R to Python in terms of symbolic math, optimization, and bootstrapping. All of these posts were pretty popular. The last one especially. Many of the commenters brought up the fact that R, while … Continue reading → [Read more...]

I’m interested in Python a lot, mostly because it appears to be wickedly fast. The downside is that I don’t know it nearly as well as R, so any speed gain in computation time is more than offset by Google … Continue reading → [Read more...]

I’m writing a post on how to draw a in 95% confidence interval in R by hand. I spent an hour or so trying to figure this out, and most message threads point someone to the ellipse() function. However, I wanted … Continue reading → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

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 → [Read more...]

I’ve only recently begun working from an evolutionary perspective, and I can’t imagine why I haven’t thought about it much before. After all, it comes up in just about everything that we do in ecology. For example, I’m currently feeding … Continue reading → [Read more...]