feasts 0.1.6

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

Improvements

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

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

The n_flat_spots() return name is now “longest_flat_spot” to better describe the feature.

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.

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

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

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.

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()

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.

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.

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)

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

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