Plotting radf models — autoplot.radf

autoplot.radf_obj takes radf_obj and radf_cv and returns a faceted ggplot object. shade is used as an input to shape_opt. shade modifies the geom_rect layer that demarcates the exuberance periods.

# S3 method for radf_obj
autoplot(
  object,
  cv = NULL,
  sig_lvl = 95,
  option = c("gsadf", "sadf"),
  min_duration = 0L,
  select_series = NULL,
  nonrejected = FALSE,
  shade_opt = shade(),
  trunc = TRUE,
  include_negative = "DEPRECATED",
  ...
)

# S3 method for radf_obj
autoplot2(
  object,
  cv = NULL,
  sig_lvl = 95,
  option = c("gsadf", "sadf"),
  min_duration = 0L,
  select_series = NULL,
  nonrejected = FALSE,
  trunc = TRUE,
  shade_opt = shade(),
  ...
)

shade(
  fill = "grey55",
  fill_negative = fill,
  fill_ongoing = NULL,
  opacity = 0.3,
  ...
)

Arguments

object: An object of class obj.
cv: An object of class cv.
sig_lvl: Significance level. It could be one of 90, 95 or 99.
option: Whether to apply the "gsadf" or "sadf" methodology (default = "gsadf").
min_duration: The minimum duration of an explosive period for it to be reported (default = 0).
select_series: A vector of column names or numbers specifying the series to be used in plotting. Note that the order of the series does not alter the order used in plotting.
nonrejected: If TRUE, plot all variables regardless of rejecting the NULL at the 5 percent significance level.
shade_opt: Shading options, typically set using shade function.
trunc: Whether to remove the period of the minimum window from the plot (default = TRUE).
include_negative: Argument name is deprecated and substituted with nonrejected.
...: Further arguments passed to ggplot2::facet_wrap and ggplot2::geom_rect for shade.
fill: The shade color that indicates the exuberance periods with positive signal
fill_negative: The shade color that indicates the exuberance periods with positive signal
fill_ongoing: The shade color that indicates the exuberance periods that are ongoing the null hypothesis.
opacity: The opacity of the shade color aka alpha.

Value

A ggplot2::ggplot()

Examples

# \donttest{
rsim_data <- radf(sim_data_wdate)
#> Using `date` as index variable.

autoplot(rsim_data)
#> Using `radf_crit` for `cv`.


# Modify facet_wrap options through ellipsis
autoplot(rsim_data, scales = "free_y", dir  = "v")
#> Using `radf_crit` for `cv`.


# Modify the shading options
autoplot(rsim_data, shade_opt = shade(fill = "pink", opacity = 0.5))
#> Using `radf_crit` for `cv`.


# Allow for nonrejected series to be plotted
autoplot(rsim_data, nonrejected = TRUE)
#> Using `radf_crit` for `cv`.


# Remove the shading completely (2 ways)
autoplot(rsim_data, shade_opt = NULL)
#> Using `radf_crit` for `cv`.

autoplot(rsim_data, shade_opt = shade(opacity = 0))
#> Using `radf_crit` for `cv`.


# Plot only the series with the shading options
autoplot2(rsim_data)
#> Using `radf_crit` for `cv`.

autoplot2(rsim_data, trunc = FALSE) # keep the minw period
#> Using `radf_crit` for `cv`.


# We will need ggplot2 from here on out
library(ggplot2)

# Change (overwrite) color, size or linetype
autoplot(rsim_data) +
  scale_color_manual(values = c("black", "black")) +
  scale_size_manual(values = c(0.9, 1)) +
  scale_linetype_manual(values = c("solid", "solid"))
#> Using `radf_crit` for `cv`.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for size is already present.
#> Adding another scale for size, which will replace the existing scale.
#> Scale for linetype is already present.
#> Adding another scale for linetype, which will replace the existing scale.


# Change names through labeller (first way)
custom_labels <- c("psy1" = "new_name_for_psy1", "psy2" = "new_name_for_psy2")
autoplot(rsim_data, labeller = labeller(.default = label_value, id = as_labeller(custom_labels)))
#> Using `radf_crit` for `cv`.


# Change names through labeller (second way)
custom_labels2 <- series_names(rsim_data)
names(custom_labels2) <- custom_labels2
custom_labels2[c(3,5)] <- c("Evans", "Blanchard")
autoplot(rsim_data, labeller = labeller(id = custom_labels2))
#> Using `radf_crit` for `cv`.


# Or change names before plotting
series_names(rsim_data) <- LETTERS[1:5]
autoplot(rsim_data)
#> Using `radf_crit` for `cv`.


# Change Theme options
autoplot(rsim_data) +
  theme(legend.position = "right")
#> Using `radf_crit` for `cv`.

 # }