Skip to contents

Lollipop Plot for Trend-Cycle Estimates

Source: R/plot_lollypop.R
lollypop.Rd

Base R (lollypop()) and ggplot2 (gglollypop()) graphics for creating lollipop plots of trend-cycle estimates alongside seasonally adjusted series.

Usage

lollypop(
  object,
  xlim = NULL,
  ylim = NULL,
  col_tc = "#E69F00",
  col_sa = "black",
  color_points = col_sa,
  cex_points = 1,
  pch_points = 16,
  xlab = "",
  ylab = "",
  lty_last_tc = 2,
  n_last_tc = 4,
  ...
)

gglollypop(
  object,
  xlim = NULL,
  ylim = NULL,
  col_tc = "#E69F00",
  col_sa = "black",
  color_points = col_sa,
  cex_points = 1,
  pch_points = 16,
  legend_tc = "Trend-cycle",
  legend_sa = "Seasonally adjusted",
  lty_last_tc = 2,
  n_last_tc = 4,
  ...
)

Arguments

object

An object of class "tc_estimates".

xlim, ylim

Limits for the x- and y-axes. If xlim is specified and ylim is NULL, ylim is determined automatically based on the truncated series.

col_sa, col_tc

Colors used for the seasonally adjusted and trend-cycle components, respectively.

color_points, cex_points

Color and size (character/numeric) of the points associated with the seasonally adjusted component.

pch_points

Point symbol type (integer or character) for the seasonally adjusted component.

xlab, ylab

Character strings for the x- and y-axis labels.

lty_last_tc

Line type for the last values of the trend-cycle component.

n_last_tc

Number of final values of the trend-cycle component to plot with a distinct line type (lty_last_tc), emphasizing higher uncertainty in recent estimates. If NULL (the default), n_last_tc is set to the Month of Cyclical Dominance (MCD) statistic.

...

Additional graphical parameters passed to internal plotting functions.

legend_tc, legend_sa

Character strings specifying the legend labels for the trend-cycle and seasonally adjusted components, respectively.

Value

  • lollypop() returns NULL invisibly and is called for its side effect (drawing a plot).

  • gglollypop() returns a ggplot object.

Details

lollypop() produces a base R graphic, whereas gglollypop() creates a ggplot2 object that can be further customized.

Examples

if (FALSE) { # rjd3jars::check_java_version(silent = TRUE)
tc_mod <- henderson_smoothing(french_ipi[, "manufacturing"])
lollypop(tc_mod, xlim = c(2022, 2024.5))
}