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feasts (development version)

feasts 0.4.1

Bug fixes

  • Fixed gg_season() not working with daily data showing seasonality > 1 week.

feasts 0.4.0

New features

  • Added gg_irf() for plotting impulse responses (typically obtained from using IRF() with fable models).
  • Added cointegration tests cointegration_johansen() and cointegration_phillips_ouliaris() from urca.

Improvements

  • Documentation improvements.

Bug fixes

  • Fixed gg_season() not wrapping across facet_period argument correctly.

feasts 0.3.2

Minor patch to resolve CRAN check issues with ggplot2 v3.5.0 breaking changes.

Improvements

  • Calculate seasonally adjusted data from classical decomposition using original data and seasonal term rather than trend and remainder.

Bug fixes

  • Fixed out-of-bounds gg_season() breaks issue with ggplot2 v3.5.0
  • Changed the metadata of classical decomposition's components to better reflect the seasonally adjusted variable's structure.

feasts 0.3.1

Minor patch to resolve CRAN check issues with S3 method consistency.

feasts 0.3.0

New features

  • Added the tapered argument to ACF() and PACF() for producing banded and tapered estimates of autocovariance (#1).

Improvements

  • gg_season() now allows seasonal period identifying labels to be nudged and repelled with the labels_repel, labels_left_nudge, and labels_right_nudge arguments.
  • gg_season() behaviour of max_col has been restored, where colours aren't used if the number of subseries to be coloured exceeds this value. The default has changed to Inf since this function now supports continuous colour guides. A new argument max_col_discrete has been added to control the threshold for showing discrete and continuous colour guides (#150).
  • Updated guerrero() method to maintain a consistent subseries length by removing the first few observations of needed. This more closely matches the described method, and the implementation in the forecast package.
  • Added grid.draw() method for ensemble graphics (gg_tsdisplay() and gg_tsresiduals()). This allows use of ggsave() with these plots (#149).

Bug fixes

  • Fixed generate(<STL>) returning $.sim as a num [1:n(1d)] instead of num [1:72] (fable/#336).
  • Fixed issue with gg_season() incorrectly grouping some seasonal subseries.
  • CCF() now matches stats::ccf() x and y arguments (#144).

feasts 0.2.2

Minor release for compatibility with an upcoming ggplot2 release. This release contains a few bug fixes and improvements to existing functionality.

Improvements

  • The gg_tsresiduals() function now allows the type of plotted residual to be controlled via the type argument.
  • Improved the default seasonal window for STL() decompositions. For data with a single seasonal pattern, the window has changed from 13 to 11. This change is based on results from simulation experiments.
  • Documentation improvements.

Bug fixes

  • Fixed issue where seasonal::seas() defaults were not being used in X_13ARIMA_SEATS() when defaults = "seasonal" (#130).
  • Fixed issue with gg_subseries() on data with spaces in the index column name (#136).

Breaking changes

  • Replaced usage of ... in ACF(), PACF(), and CCF() with y (and x for CCF()) arguments. This change should not affect the code for most users, but is important for the eventual passing of ... to acf(), pacf() and ccf() in a future version (#124).

feasts 0.2.1

Small patch to fix check issues on Solaris, and to resolve components() for automatically selected transformations in X_13ARIMA_SEATS().

feasts 0.2.0

New features

  • Added X_13ARIMA_SEATS() decomposition method. This is a complete wrapper of the X-13ARIMA-SEATS developed by the U.S. Census Bureau, implemented via the seasonal::seas() function. The defaults match what is used in the seasonal pacakge, however these defaults can be removed (giving an empty default model) by setting defaults="none".

Breaking changes

  • The new X_13ARIMA_SEATS() method officially deprecates (supersedes) the X11() and SEATS() models which were previously not exported (#66).

Improvements

  • Documentation improvements.

feasts 0.1.7

New features

  • Added generate() method for STL() decompositions. The method uses a block bootstrap method to sample from the residuals.
  • Added fitted() and residuals() methods for STL() decompositions.

Improvements

  • Changed guerrero() default lower bound for Box-Cox lambda selection to from -1 to -0.9. A transformation parameter of -1 typically results from data which should not be transformed with a Box-Cox transformation, and can result in very inaccurate forecasts if such a strong and inappropriate transformation is used.
  • Improved time series plotting functions axis labelling.
  • Documentation improvements.

feasts 0.1.6

A minor release to fix check issues introduced by changes in an upstream dependency.

Improvements

  • gg_season() labels are low aligned outward (#115).

Bug fixes

  • Fixed issue with plotting aggregated tsibbles with gg_season() and gg_subseries() (#117).
  • Fixed occasional issue with double label/breaks displayed in gg_season()

feasts 0.1.5

Improvements

  • gg_lag() facets are now displayed with a 1:1 aspect ratio.
  • Season and subseries plots of numeric index data now starts at the earliest measured observation, rather than assuming a meaningful 0 (#111).
  • The n_flat_spots() function has been renamed to longest_flat_spot() to more accurately describe the feature.
  • gg_season() and ggsubseries() date structure improvements.
  • Documentation improvements

Breaking changes

  • The n_flat_spots() return name is now "longest_flat_spot" to better describe the feature.

Bug fixes

  • Fixed spectral density plot in gg_tsdisplay() erroring when the spec.ar order is chosen to be 0.
  • Fixed CCF() lag being spaced by multiples of the data's frequency.
  • Fixed labelling of x-axis for gg_season() and gg_subseries() (#107).
  • Fixed View() not working on ACF(), PACF() and CCF() outputs.

feasts 0.1.4

Minor patch to resolve upstream check issues introduced by dplyr v1.0.0 and tsibble v0.9.0.

New features

  • Circular time plots are now supported by setting polar = TRUE in gg_season().

Improvements

  • Added partial matching of the type argument in ACF().
  • Updated feat_spectral() to use stats::spec.ar() instead of ForeCA::spectral_entropy(). Note that the feature value will be slightly different due to use of a different spectral estimator, and the fix of a bug in ForeCA.

Bug fixes

  • Fixed the minimum data length for seasonal estimation in feat_stl().

feasts 0.1.3

Improvements

  • The axis for gg_lag() have been reversed for consistency with stats::lag.plot().
  • Graphical improvements for displaying weekly seasonality in season and subseries plots.
  • Added intermittency features available in feat_intermittent()

Bug fixes

  • Fixed the sprectral density plot in gg_tsdisplay() not working with plotting expressions of data.
  • Fixed issue with gg_subseries() erroring when certain column names are used (#95).
  • Fixed issue with environment handling in STL() specials.

feasts 0.1.2

Improvements

  • var_tiled_var() no longer includes partial tile windows in the computation.
  • Added residual acf features to feat_stl().
  • Performance improvements.

Breaking changes

  • Decompositions are now treated as models. To access the decomposed values, you will now have to use components(). For example, tourism %>% STL(Trips) is now tourism %>% model(STL(Trips)) %>% components(). This change allows for more flexible decomposition specifications, and better interfaces for decomposition modelling.

Bug fixes

  • Fixed bug with feat_spectral() not showing results.
  • Fix warning in ACF(), PACF() and CCF() for tidyr change.
  • gg_tsdisplay() will no longer fail on non-seasonal data with missing values. The last plot will instead show a PACF in this case (#76)
  • Better handling of perfect fits in stat_arch_lm() (#85)

feasts 0.1.1

Improvements

  • Better naming of seasonal columns in STL decomposition when seasonal period is specified.

Bug fixes

  • Fixes issues with running tests on unsupported systems.

feasts 0.1.0

  • First release.

New features

  • Added support for graphical analysis of tidy temporal data and models, with gg_season, gg_subseries, gg_lag, gg_tsdisplay, gg_tsresiduals, gg_arma.
  • Added support for autocorrelation functions and plots, with ACF, PACF, CCF, and autoplot.tbl_cf
  • Added a collection of features to be used with fabletools::features(): feat_stl, feat_acf, feat_pacf, guerrero, unitroot_kpss, unitroot_pp, unitroot_ndiffs, unitroot_nsdiffs, box_pierce, ljung_box, var_tiled_var, var_tiled_mean, shift_level_max, shift_var_max, shift_kl_max, feat_spectral, n_crossing_points, n_flat_spots, coef_hurst, stat_arch_lm
  • Added support for two decomposition methods: classical_decomposition, STL