# Lab Notes

This section includes links to various notes I've put together as part of my work. They are organized by date, and include a short description. Feel free to contact me with any questions or comments you have about them, or to reuse or redistribute the material in ways that are helpful.

22 March 2023: An attempt at a locally linear (ODE) metacommunity model. Sadly gets bogged down in a somewhat too complex spatial moment model. <link>

9 October 2022: R script for changing the order of elements in file names based on a separator (e.g. "_"). <link>

4 September 2022: LaTeX code used for making my CV. <link>

2 September 2022: Example script for estimating the Lyapunov exponent of a process using the rEDM package. <code>

8 January 2022: Notes on COVID growth rates in the Omicron surge following super-exponential growth. <link> <code> <data>. See Chapter 5.4 in the Lehman et al. eBook for details on the model <link>.

3 June 2021: Very simple code for measuring light intensity with an Arduino, adapted from James Carlson. <link>

8 April 2021: An example showing when random effects that overlap perfectly with a categorical variable can lead to biased estimates (at least for lme4, the result is that the fixed effect is correctly estimated, but the random effect is set to zero). <link>

23 March 2021: A short discussion on how to measure the rates of an exponential process, either in terms of averages or half-lifes (and why half-lives are better). <link>

7 March 2021: A basic SIR model with re-infection. <link>

13 February 2021: A very simple power analysis comparing results from the recent study on AstraZeneca vaccine efficacy against the B.1.351 "South African" COVID variant. <link>

3 February 2021: An extended example for power analysis, showing how to deal with multivariate predictors. <link>

28 July 2020: Transforming Lotka-Volterra parameters from the linearized to the classic formulation - shows a short example with two species. <link>

11 May 2020: Weird things that R does - A compilation of notes related to R's many irrationalities that can stymie people who are just starting out with it, and some of my solutions for these problems. <link>

19 April 2020: A comparison of fitting methods for projecting a logistic growth curve, inspired by this post. Interestingly, the simple rate based fitting method performs much worse than a state-based method, which I would not have thought. <link>

21 March 2020: A more polished version of the SIR model, for making short-term forecasts in a few countries. Please see disclaimers in the file. <link>

10 March 2020: Update, testing per-capita growth rate of COVID-19 vs. number of cases. Requires data from the CSSEGISandData 'COVID-19' GitHub, available at https://github.com/CSSEGISandData/COVID-19. <link>

24 February 2020: A basic SIR model, based on rough current data about COVID-19. Note that this model assumes no changes in behavior or uncertainty in rate estimates, and is therefore highly unrealistic (i.e. don't take the forecast too seriously). <link>

9 January 2020: Some basic notes on applying power analyses with binary and continuous data. <link>

14 November 2019: Some example code and data for analyzing human population growth, and the competition/predation data from Gause 1934. For use as part of the Fall 2019 ecology course at Halle. <zip>

17 September 2019: Some notes on coexistence and stability that I've assembled as part of literature reviews for a few projects that I am working on. <pdf>

2 September 2019: Somewhat trivial simulation showing expected uptake of light by individual species in a multi-species mixed canopy. <R>

15 July 2019: Example analysis in response to a recent paper on potential logit regression, tweeted by Forian Hartig (thread available here). <R>