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About | Datavore Consulting

Math, programming, ecology, and more. Datavore Consulting was a short-lived business venture by a few friends (Travis Hinkelman, Ben Nolting, Caroline Hinkelman, Tony Mong) with a shared love of math, programming, and ecology. We have decided to focus on our primary careers, but Travis and Ben will continue to blog under the Datavore Consulting banner. Travis Hinkelman is currently an ecological modeler with Cramer Fish Sciences. Ben Nolting is currently a post-doctoral researcher. Using paste to read an...

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About | Datavore Consulting | datavoreconsulting.com Reviews

https://datavoreconsulting.com

Math, programming, ecology, and more. Datavore Consulting was a short-lived business venture by a few friends (Travis Hinkelman, Ben Nolting, Caroline Hinkelman, Tony Mong) with a shared love of math, programming, and ecology. We have decided to focus on our primary careers, but Travis and Ben will continue to blog under the Datavore Consulting banner. Travis Hinkelman is currently an ecological modeler with Cramer Fish Sciences. Ben Nolting is currently a post-doctoral researcher. Using paste to read an...

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Datavore Consulting

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Math, programming, ecology, and more. Limitations of the negative binomial distribution in spatial models. Suppose that you want to create a model that generates spatial locations of trees. You want the model to be stochastic, so that each time you generate a forest, you end up with a different configuration of trees. The relevant tool is a spatial point process; mathematical details are described in books such as Daley and Veres-Jones. Each forest that you generate is called a realization of the process.

2

Volume Rendering and Large Data Sets | Datavore Consulting

http://datavoreconsulting.com/general/volumetric-rendering-mathematica

Math, programming, ecology, and more. Volume Rendering and Large Data Sets. Volume rendering, a new feature in Mathematica 9, provides an efficient way to visualize very large data sets. I first learned of this feature from reading Jeffery Bryant’s post. In today’s post, we will use volume rendering for a more prosaic example: color analysis of a photo of puppies. Our picture is not huge, so plotting points would work. With very large data sets, though, plotting individual points becomes unmanageable...

3

Count data and GLMs: choosing among Poisson, negative binomial, and zero-inflated models | Datavore Consulting

http://datavoreconsulting.com/programming-tips/count-data-glms-choosing-poisson-negative-binomial-zero-inflated-poisson

Math, programming, ecology, and more. Count data and GLMs: choosing among Poisson, negative binomial, and zero-inflated models. Ecologists commonly collect data representing counts of organisms. Generalized linear models (GLMs) provide a powerful tool for analyzing count data. [As mentioned previously. You should generally not transform your data to fit a linear model and, particularly, do not log-transform count data. No of samples per treatment. Mean count for treatment A. Mean count for treatment B.

4

Zing! Mathematica one-liners | Datavore Consulting

http://datavoreconsulting.com/programming-tips/zing

Math, programming, ecology, and more. I love the elegant simplicity of programming in Mathematica. There is something undeniably beautiful about accomplishing something complex in a concise chunk of code. A famous Mathematica mantra is, “if you are using a For loop, you are probably doing it wrong.” I encourage Mathematica programmers to keep that in mind. And download a notebook of the programs here. For those who work in biological modelling, I recommend checking Yves Klett’s. At University of Nebraska.

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Numerically solving PDEs in Mathematica using finite difference methods | Datavore Consulting

http://datavoreconsulting.com/programming-tips/numerically-solving-pdes-mathematica-finite-differences

Math, programming, ecology, and more. Numerically solving PDEs in Mathematica using finite difference methods. Sadly, some types of PDEs are beyond NDSolve’s capabilities. Confronted with one of these PDEs, a user must resort to a more “manual” procedure to find a numerical solution. In this post, we’ll examine a few tricks that can make this process easier. Consider the following PDE:. We seek a solution,. Xgrid = Range[0, 10]; ygrid = Range[0, 10]; grid = Outer[{#1, #2} &;, xgrid, ygrid];. At each grid...

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About | Datavore Consulting

Math, programming, ecology, and more. Datavore Consulting was a short-lived business venture by a few friends (Travis Hinkelman, Ben Nolting, Caroline Hinkelman, Tony Mong) with a shared love of math, programming, and ecology. We have decided to focus on our primary careers, but Travis and Ben will continue to blog under the Datavore Consulting banner. Travis Hinkelman is currently an ecological modeler with Cramer Fish Sciences. Ben Nolting is currently a post-doctoral researcher. Using paste to read an...

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