forecast package v6.2

October 20, 2015
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(This article was first published on Hyndsight » R, and kindly contributed to R-bloggers)

It is a while since I last updated the CRAN version of the forecast package, so I uploaded the latest version (6.2) today. The github version remains the most up-to-date version and is already two commits ahead of the CRAN version.

This update is mostly bug fixes and additional error traps. The full ChangeLog is listed below.

  • Many unit tests added using testthat.
  • Fixed bug in ets() when very short seasonal series were passed in a data frame.
  • Fixed bug in nnetar() where the initial predictor vector was reversed.
  • Corrected model name returned in nnetar().
  • Fixed bug in accuracy() when non-integer seasonality used.
  • Made auto.arima() robust to non-integer seasonality.
  • Fixed bug in auto.arima() where allowmean was ignored when stepwise=FALSE.
  • Improved robustness of forecast.ets() for explosive models with multiplicative trends.
  • Exogenous variables now passed to VAR forecasts
  • Increased maximum nmse in ets() to 30.
  • Made tsoutliers() more robust to weak seasonality
  • Changed tsoutliers() to use supsmu on non-seasonal and seasonally adjusted data.
  • Fixed bug in tbats() when seasonal period 1 is a small multiple of seasonal period 2.
  • Other bug fixes

Thanks to David Shaub for contributing most of the unit tests.

Please submit bug reports and feature requests to the github page. Don’t forget to provide a minimal reproducible example for any bug reports.

To leave a comment for the author, please follow the link and comment on their blog: Hyndsight » R.

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