forecast package v6.2
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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()
whereallowmean
was ignored whenstepwise=FALSE
. - Improved robustness of
forecast.ets()
for explosive models with multiplicative trends. - Exogenous variables now passed to VAR forecasts
- Increased maximum
nmse
inets()
to 30. - Made
tsoutliers()
more robust to weak seasonality - Changed
tsoutliers()
to usesupsmu
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.
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