Time Series Forecasting Best Practices & Examples
In this release, we added a new example to the R codebase, and continued to harden the quality and testing of the codebase from previous release. The added example is an introduction to forecasting with the Tidyverts framework, using monthly Australian retail turnover by state and industry code. The dataset is one of many included in the tsibbledata
package of example time series datasets, which we wanted to introduce to the users through this added example. Another bigger change to the repository is a greatly improved unit test coverage for the fclib
module, and we also included coverage computation in our build pipelines. Additionally, we addressed a number of bugs and issues raised by the repository users, for which we are greatly thankful. Detailed changes included in this release are outlined below.
tsibbledata::aus_retail
dataset. It also includes a closing comment on the hazards of forecasting in the presence of COVID-19. #200pmdarima
package #211environment_setup.sh
to stop execution if conda env is not created #194TSPerf - a repository of time-series forecasting models with a comprehensive comparison of their performance over provided benchmark data sets, implemented on Azure.