Blog Archives

First Impressions of Shiny, an R Package

October 18, 2016
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Today I wanted to try something new; so instead of discussing a project, let’s briefly take a look at an R Package I’ve recently discovered. Before we being let me just mention that I realize not everyone uses R or have even used it before, instead my focus here will be on the technology, innovation,

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The benefits of interdisciplinarity: residence time

October 18, 2016
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The benefits of interdisciplinarity: residence time

The so-called residence time of a system is both an immensely useful and highly intuitive conception which provides a relevant timescale for processes. For example, the residence time of nutrients flowing into a pond would be the average ‘lifetime’ of the nutrients before being taking up by the pond creatures. If it is a small

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Analyzing YSI data through clustering

October 8, 2015
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Analyzing YSI data through clustering

Update 10/13/15 – Minor improvements to code and an update to the latest findings. CTD data (conductivity, temperature and depth) from a YSI provides a quick and methodologically simple way to estimate the current water column state by, literally, dropping an instrument off the side of a boat. During each deployment the YSI records the

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The Future of R (the good, bad, and ugly)

October 3, 2015
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The Future of R (the good, bad, and ugly)

On a day to day basis, I use the R programing language more than any other language (e.g Python, Java, Fortran, Matlab…), and there is a good reason for it: R excels at the sort of work I do. It has been extremely well suited to my modeling work, especially when going to analyze the

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Markov Chain Monte Carlo: A Practical Introduction

August 17, 2015
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Markov Chain Monte Carlo: A Practical Introduction

Markov Chain Monte Carlo simulation sounds, admittedly, like a method better left to professional practitioners and the like; but please don’t let the esoteric name fool you. MCMC, as we like to call is, is a powerful yet deceptively simple technique that can be useful in problems ranging throughout science and engineering. Since this promises

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Finalizing my research, the CCELIM model, in R

August 10, 2015
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For the past 6 months I’ve been working on an inverse modeling project as a ‘starter’ graduate project, and today I am announcing that I can see the light at the end of the tunnel. While there is certainly more work ahead, especially with regards to the manuscript,  the model and the code are just

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Which Witch is Which

May 29, 2015
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Which Witch is Which

This post is an elaboration of an iRKernel Notebook which can be found at http://misc.tkelly.org/Which_Witch.html. For a previous article on the iPython Notebook, see here. Every programming language comes pre-packaged with certain basic functions, or methods, that are considered standard. These generally include methods for sorting objects, conversions between basic types (e.g. integer float string),

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Making R your own: Scripting & Tweeting

May 21, 2015
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Previously I have spoke on the merits of the R programing language (here) and alluded to its place in my research (here)(1)I also showed how I used it with some of my excursions into Computational Fluid Dynamics here and previously here. , so today I thought it was about time to share how I approach using

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Optimizing R Code in my Model

May 7, 2015
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Optimizing R Code in my Model

Recently I have been talking a fair bit about my inverse modeling work, so now that it’s summer I finally have time to clean up the code base. Now that the code is working fairly well and offers all of the main features that I can think of, the goal is to get it running

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How Twitter Improved my Ecological Model

February 26, 2015
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How Twitter Improved my Ecological Model

For a last couple weeks I’ve been working on a marine ecosystem model using a technique called Inverse Modeling(1)I’ll be sure to do a writeup on what Inverse Modeling is and what makes it interesting in the future.; and while there’s been lots of progress, I’m starting to get to the point where the model takes some

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