This two full-day workshop provides the basics of time series analysis and forecasting in R. This workshop is part of the NYR 2023 event, and will run in-person at Columbia University on the 11-12th July 2023.
Registration is available at https://rstats.ai/nyr.
Tickets to the workshop are sold separately from the conference.
Attendees will learn:
- How to wrangle time series data with familiar tidy tools.
- How to compute time series features and visualize large collections of time series.
- How to select a good forecasting algorithm for your time series.
- How to ensure forecasts of a large collection of time series are coherent.
The workshop will provide a quick-start overview of exploring time series data and producing forecasts. There is no need for prior experience in time series to get the most out of this workshop.
It is expected that you are comfortable with writing R cod and using tidyverse packages including dplyr and ggplot2. If you are unfamiliar with writing R code or using the tidyverse, consider working through the learnr materials here: https://learnr.numbat.space/.
Some familiarity with statistical concepts such as the mean, variance, quantiles, normal distribution, and regression would be helpful to better understand the forecasts, although this is not strictly necessary.
Please bring your own laptop capable of running R.
To be able to complete the exercises of this workshop, please install a suitable IDE (such as RStudio), a recent version of R (4.1+) and the following packages.
- Time series packages and extensions
- fpp3, sugrrants
- tidyverse packages and friends
- tidyverse, fpp3
The following code will install the main packages needed for the workshop.
install.packages(c("tidyverse","fpp3", "GGally", "sugrrants"))Please have the required software installed and pre-work completed before attending the workshop.