Tidy forecasting in R
The fable package for doing tidy forecasting in R is now on CRAN. Like tsibble and feasts, it is also part of the tidyverts family of packages for analysing, modelling and forecasting many related time series (stored as tsibbles). For a brief introduction to tsibbles, see this post from last month. Here we will forecast Australian tourism data by state/region and purpose. This data is stored in the tourism tsibble where Trips contains domestic visitor nights in thousands.Feature-based time series analysis
In my last post, I showed how the feasts package can be used to produce various time series graphics. The feasts package also includes functions for computing FEatures And Statistics from Time Series (hence the name). In this post I will give three examples of how these might be used. library(tidyverse) library(tsibble) library(feasts) Exploring Australian tourism data I used this example in my talk at useR!2019 in Toulouse, and it is also the basis of a vignette in the package, and a recent blog post by Mitchell O’Hara-Wild.Recent publications
- Anastasios Panagiotelis, Puwasala Gamakumara, George Athanasopoulos, Rob J Hyndman (2019) Forecast reconciliation: A geometric view with new insights on bias correction. Abstract pdf
- Priyanga Dilini Talagala, Rob J Hyndman, Catherine Leigh, Kerrie Mengersen and Kate Smith-Miles (2019) A feature-based framework for detecting technical outliers in water-quality data from in situ sensors. Water Resources Research, to appear. Abstract pdf
- Catherine Leigh, Sevvandi Kandanaarachchi, James M McGree, Rob J Hyndman, Omar Alsibai, Kerrie Mengersen, Erin E Peterson (2019) Predicting sediment and nutrient concentrations in rivers using high-frequency water quality surrogates. PLOS ONE, to appear. Abstract pdf
- Sevvandi Kandanaarachchi, Rob J Hyndman (2019) Dimension reduction for outlier detection using DOBIN. Abstract pdf
Recent and upcoming seminars
- Tidy time series analysis in R. (27 September 2019) More info...
- Feature-based time series analysis. (27 September 2019) More info...
- Tidy time series analysis in R. (26 September 2019) More info...
- Forecasting is not prophecy: dealing with high-dimensional probabilistic forecasts in practice. (21 August 2019) More info...