Plotting Methods for Trend-Cycle Estimates — plot.tc

Plotting methods for objects of class "tc_estimates". plot() and lines() produce base R graphics, whereas autoplot() creates a ggplot2 object.

Usage

# S3 method for class 'tc_estimates'
plot(
  x,
  y = NULL,
  xlim = NULL,
  ylim = NULL,
  col_tc = "#E69F00",
  col_sa = "black",
  xlab = "",
  ylab = "",
  lty_last_tc = 2,
  n_last_tc = 4,
  ...
)

# S3 method for class 'tc_estimates'
lines(x, col_tc = "#E69F00", lty_last_tc = 2, n_last_tc = 4, ...)

# S3 method for class 'tc_estimates'
autoplot(
  object,
  xlim = NULL,
  ylim = NULL,
  col_tc = "#E69F00",
  col_sa = "black",
  legend_tc = "Trend-cycle",
  legend_sa = "Seasonally adjusted",
  lty_last_tc = 2,
  n_last_tc = 4,
  ...
)

# S3 method for class 'ts'
autoplot(object, xlim = NULL, ylim = NULL, ...)

Arguments

x: An object of class "tc_estimates".
y: Unused parameter, kept for compatibility with the generic function.
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.
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.
object: An object of class "tc_estimates".
legend_tc, legend_sa: Character strings specifying the legend labels for the trend-cycle and seasonally adjusted components, respectively.

Value

plot() and lines() return NULL invisibly and are called for their side effect (drawing a plot).
autoplot() returns a ggplot object.

Details

plot.tc_estimates() and autoplot.tc_estimates() produce a plot showing both the seasonally adjusted series and the estimated trend-cycle component. lines.tc_estimates() adds only the trend-cycle component to an existing base R plot.

Examples

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