This week Bryan Shalloway presented a talk about feature engineering with sliding windows and lagged inputs. You can find a post on his personal blog about the topic here, and the link to the corresponding GitHub repository here.

By Matt Brousil In this post I'll walk through some of the basics for getting started importing, formatting, and creating maps with spatial data in R. Many students and researchers I know (myself included) have taken GIS coursework and are familiar with tools like ArcMap, but want to work with their data in R. R …

By Mikala Meize Libraries used 1library(tidyverse) 2library(ggthemes) The ggplot() function, which is used in this tutorial is housed within the tidyverse library. The ggthemes library is something we'll use later on in the tutorial. There are several ways to set up a plot using ggplot(). The first is to simply run: …

By Mikala Meize Libraries used 1library(QuantPsyc) 2library(lmtest) 3library(palmerpenguins) Linear model information Linear models are generally coded in this format: model.name <- modeltype(outcome ~ predictor, data, specifications) The following code will apply specifically to Ordinary Least Squares (OLS) …

By Nicholas A. Potter This is a short introduction to using data.table based on my work with climate data. Initial setup Let's begin by generating some data to work with. We'll use the following packages: 1# If you don't have the packages below, install with: 2#install.packages(c("data.table", …

By Abigail Hudak Overview The goal of this document is to share some tips and ideas about structuring and cleaning data for sharing and collaborating. None of the concepts are comprehensive, but I hope you find some useful tips. Cleaning data Favorites of janitor The package janitor is awesome for data cleaning. …

By Matt Brousil For the blog post accompanying this week's Intro to Shiny talk, please visit our previous post about Shiny: https://cougrstats.netlify.app/post/how-to-shiny-2/

By Matt Brousil This week I'm going to walk through some examples of applying functions to every item in one (or more) lists. Basically this gives an overview answering the question: "If I have a list of data, how do I loop through that list manipulating and running analyses on its data without using for() …

By Ben Lee Data for this walkthrough are available here. Why Use an SEM? Autocorrelation is everywhere in Ecological data, and fundamentally violates the assumptions of univariate linear models. Path analysis allows us to partition the variance of responses through a series of linear models. In our example, we'll be …