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Plot Growth Rates for Trend-Cycle Estimates

Source: R/plot_growth.R
growthplot.Rd

Base R (growthplot()) and ggplot2 (gggrowthplot()) graphics for plotting the growth rates of the trend-cycle estimates (solid lines) and the seasonally adjusted series (bar-lines or lines).

Usage

growthplot(
  object,
  pct = TRUE,
  xlim = NULL,
  ylim = NULL,
  col_tc = "#E69F00",
  col_sa = "black",
  xlab = "",
  ylab = "",
  sa_bar_line = TRUE,
  ...,
  lag = -1
)

gggrowthplot(
  object,
  pct = TRUE,
  xlim = NULL,
  ylim = NULL,
  sa_bar_line = TRUE,
  col_tc = "#E69F00",
  col_sa = "black",
  col_sa_fill = "grey",
  legend_tc = "Trend-cycle",
  legend_sa = "Seasonally adjusted",
  ...,
  lag = -1
)

Arguments

object

An object of class "tc_estimates".

pct

Logical. If TRUE (the default), the growth rate is expressed as a percentage, otherwise as a ratio.

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.

xlab, ylab

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

sa_bar_line

Logical. If TRUE (the default), the growth rates of the seasonally adjusted series are presented as bar-lines; otherwise, as lines.

...

Additional graphical parameters passed to internal plotting functions.

lag

Integer specifying the lag used to compute the growth rate. Defaults to -1 (i.e., period-to-period growth rate).

col_sa_fill

Fill color of the bars for the seasonally adjusted series.

legend_tc, legend_sa

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

Value

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

  • gggrowthplot() returns a ggplot object.

Details

growthplot() produces a base R graphic, whereas gggrowthplot() 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"])
growthplot(tc_mod, xlim = c(2022, 2024.5))
}