Presentation at the International Symposium on Forecasting, Thessaloniki, Greece, and at useR!2019, Toulouse, France.
Modern time series are often high-dimensional and observed at high frequency, but most existing R packages for time series are designed to handle low-dimensional and low frequency data such as annual, monthly and quarterly data. The feasts package is part of new collection of tidyverts packages designed for modern time series analysis using the tidyverse framework and structures. It uses the tsibble package to provide the basic data class and data manipulation tools.
The feasts package provides Feature Extraction And Statistics for Time Series, and includes tools for exploratory data analysis, data visualization, and data summary. For example, it includes autocorrelation plots, seasonality plots, time series decomposition, tests for units roots and autocorrelations, etc.
I will demonstrate the design and use of the feasts package using a variety of real data, highlighting its power for handling large collections of related time series in an efficient and user-friendly manner.