R

rEDM Tutorial

Agenda Resources Installation and Setup Backup option Data Formats Determine embedding dimension using Simplex Projection Identify nonlinearity using S-map Multivariate Models Convergent Cross Mapping Surrogate Analysis with CCM Extra topics These are the notes for the rEDM tutorial I gave at the November 13-15 Nonlinear Dynamics and Fisheries Workshop at the NMFS Southwest Fisheries Science Center in Santa Cruz. Agenda Time 900-915 set up computers 915-930 data formats 930-945 simplex, plotting rho vs.

Advice on Data Analysis in R

While on my visit to the University of Nebraska, Lincoln, I had the pleasure of taking over Chris Chizinski’s R class on Friday (2018-11-02). I demo’d a few things about setting up RStudio, using RStudio packages and the here package, and then walked through a workflow of doing data analysis, converting code into functions, and writing scripts and functions to be more accessible for readers. For reference, here are my slides.

Deploying package documentation with pkgdown and Travis CI

For my rEDM package, I’ve been using the pkgdown package to build a website comprising all the documentation and vignettes, for easy reference from a web browser. The normal workflow for this is something like: Make updates to the package. Run pkgdown::build_site() to generate the website files into a docs folder. Commit changes and upload to GitHub. Use GitHub Pages, configured to source the files from the docs folder on the master branch.

Guide for Using an R Package for Reproducible Research

Motivation What I used to do Why use an R package? How-to Guide Requirements Tutorial Setup Workflow Bonus steps Other Readings Motivation I’ve been wondering about the best way to organize (reproducible) research projects in R for a while now. I figured this might be a good spot to write up some thoughts. What I used to do Initially my projects would consist of just a few R files that separate out functions from a main script that calls the functions.

Making gifs in R with `gganimate`

Introduction Package Setup Data Forecasting Generate data to plot Figure Introduction Since I’m writing R code to make certain figures for this website, I thought I could go ahead and annotate some of it in R markdown to serve as blog posts. Package Setup library(tidyverse) ## ── Attaching packages ────────────────────────────────────────────────────────────── tidyverse 1.2.1 ── ## ✔ ggplot2 3.0.0.9000 ✔ purrr 0.2.5 ## ✔ tibble 1.4.2 ✔ dplyr 0.