forecast 9.0.0

• ets() now allows missing values in the time series (#952)
• Added mean_model() and forecast.mean_model()
• Added rw_model() and forecast.rw_model() (m-muecke, #969)
• Added spline_model() and forecast.spline_model() (#1013)
• Added theta_model() and forecast.theta_model() (#1014)
• Added croston_model() and forecast.croston_model() (#1015)
• Added simulated and bootstrapped prediction intervals to more models (#1040)
• Added parallelization for nnetar (m-muecke, #346)
• More consistent handling of biasadj across models
• accuracy() rewritten to use S3 methods for models and remove accuracy.default() (#912)
• Bug fixes and performance improvements
• Documentation improvements

forecast 8.24.0

• Documentation improvements
• Bug fixes

forecast 8.23.0

• Prevented RNG state changing when the package is attached (#954, #955).
• head.ts and tail.ts only defined for R < 4.5.0 due to new base R functions.

forecast 8.22.0

• hfitted now much faster for ARIMA models (danigiro, #949)
• hfitted now much faster for ETS models, and produces fitted values from
  initial states (#950)

forecast 8.21.1

• nnetar now allows p or P to be 0
• Bug fixes and improved docs

CRAN 8.21

v8.21

Updated docs

CRAN 8.19

• Bug fixes

CRAN 8.18

• Updated RW forecasts to use an unbiased estimate of sigma2
• Bug fixes

CRAN v8.17

Updated CRAN submission date

CRAN v8.16

• Fixed tslm() incorrectly applying Box-Cox transformations when an mts
  is provided to the data argument (#886).
• Set D=0 when auto.arima applied to series with 2m observations or fewer.
• Improved performance of parallel search of ARIMA models (jonlachmann, #891).
• Fixed scoping of functions used in ggAcf() (#896).
• Fixed checks on xreg in simulate.Arima() (#818)
• Improved docs and bug fixes.