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Tidy time series forecasting
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R Fixed error with tidying rank deficient fits Mar 21, 2019
inst Updated wordlist Feb 22, 2019
man Reexported fablelite verbs Mar 19, 2019
src Removed binary objects. Sep 25, 2018
tests Updated nnetar tests for box_cox rename Mar 11, 2019
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.gitignore used tic for pkgdown site Feb 19, 2019
DESCRIPTION * added cran badge Feb 25, 2019
NAMESPACE Reexported fablelite verbs Mar 19, 2019
README.Rmd Fixed README missing tsibble package load Mar 13, 2019
appveyor.yml used tic for pkgdown site Feb 19, 2019
codecov.yml Added codecov Aug 21, 2018
fable.Rproj Renamed package to fable 🎉 Jun 1, 2018
tic.R used tic for pkgdown site Feb 19, 2019


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The R package fable provides methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling. Data, model and forecast objects are all stored in a tidy format.


You can install the development version from GitHub

# install.packages("devtools")

Installing this software requires a compiler


aus_retail %>%
    State %in% c("New South Wales", "Victoria"),
    Industry == "Department stores"
  ) %>% 
    ets = ETS(box_cox(Turnover, 0.3)),
    arima = ARIMA(log(Turnover)),
    snaive = SNAIVE(Turnover)
  ) %>%
  forecast %>% 
  autoplot(filter(aus_retail, year(Month) > 2010), level = NULL)

You can read more about the functionality of this package and the ideas behind it here:

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