gg_tsdisplay: Ensemble of time series displays

Description

Plots a time series along with its ACF along with an customisable third graphic of either a PACF, histogram, lagged scatterplot or spectral density.

Usage

gg_tsdisplay(
  data,
  y = NULL,
  plot_type = c("auto", "partial", "season", "histogram", "scatter", "spectrum"),
  lag_max = NULL
)

Value

A list of ggplot objects showing useful plots of a time series.

Arguments

data: A tidy time series object (tsibble)
y: The variable to plot (a bare expression). If NULL, it will automatically selected from the data.
plot_type: type of plot to include in lower right corner. By default ("auto") a season plot will be shown for seasonal data, a spectrum plot will be shown for non-seasonal data without missing values, and a PACF will be shown otherwise.
lag_max: maximum lag at which to calculate the acf. Default is 10*log10(N/m) where N is the number of observations and m the number of series. Will be automatically limited to one less than the number of observations in the series.

Author

Rob J Hyndman & Mitchell O'Hara-Wild

References

Hyndman and Athanasopoulos (2019) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia. https://OTexts.com/fpp3/

Examples

Run this code

library(tsibble)
library(dplyr)
tsibbledata::aus_retail %>%
  filter(
    State == "Victoria",
    Industry == "Cafes, restaurants and catering services"
  ) %>%
  gg_tsdisplay(Turnover)

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