cartesian_rolling {Wats} | R Documentation |
Linear Plot with Rolling Summaries
Description
Shows the interrupted time series in Cartesian coordinates without a periodic/cyclic components.
Usage
cartesian_rolling(
ds_linear,
x_name,
y_name,
stage_id_name,
rolling_lower_name = "rolling_lower",
rolling_center_name = "rolling_center",
rolling_upper_name = "rolling_upper",
palette_dark = NULL,
palette_light = NULL,
color_sparse = grDevices::adjustcolor("tan1", 0.5),
change_points = NULL,
change_point_labels = NULL,
draw_jagged_line = TRUE,
draw_rolling_line = TRUE,
draw_rolling_band = TRUE,
draw_sparse_line_and_points = TRUE,
jagged_point_size = 2,
jagged_line_size = 0.5,
rolling_line_size = 1,
sparse_point_size = 4,
sparse_line_size = 0.5,
band_alpha = 0.4,
change_line_alpha = 0.5,
change_line_size = 3,
title = NULL,
x_title = NULL,
y_title = NULL
)
Arguments
ds_linear |
The data.frame to containing the data. |
x_name |
The variable name containing the date. |
y_name |
The variable name containing the dependent/criterion variable. |
stage_id_name |
The variable name indicating which stage the record belongs to.
For example, before the first interruption, the |
rolling_lower_name |
The variable name showing the lower bound of the rolling estimate. |
rolling_center_name |
The variable name showing the rolling estimate. |
rolling_upper_name |
The variable name showing the upper bound of the rolling estimate. |
palette_dark |
A vector of colors used for the dark/heavy graphical elements.
The vector should have one color for each |
palette_light |
A vector of colors used for the light graphical elements.
The vector should have one color for each |
color_sparse |
The color of the 'slowest' trend line, which plots only one value per cycle. |
change_points |
A vector of values indicate the interruptions between stages. It typically works best as a Date or a POSIXct class. |
change_point_labels |
The text plotted above each interruption. |
draw_jagged_line |
A boolean value indicating if a line should be plotted that connects the observed data points. |
draw_rolling_line |
A boolean value indicating if a line should be plotted
that connects the rolling estimates specified by |
draw_rolling_band |
A boolean value indicating if a band should be plotted
that envelopes the rolling estimates (whose values are take from the
|
draw_sparse_line_and_points |
A boolean value indicating if the sparse line and points should be plotted. |
jagged_point_size |
The size of the observed data points. |
jagged_line_size |
The size of the line connecting the observed data points. |
rolling_line_size |
The size of the line connecting the rolling estimates. |
sparse_point_size |
The size of the sparse estimates. |
sparse_line_size |
The size of the line connecting the sparse estimates. |
band_alpha |
The amount of transparency of the rolling estimate band. |
change_line_alpha |
The amount of transparency marking each interruption. |
change_line_size |
The width of a line marking an interruption. |
title |
The string describing the plot. |
x_title |
The string describing the x-axis. |
y_title |
The string describing the y-axis. |
Value
Returns a ggplot2 graphing object
Examples
library(Wats) # Load the package
change_month <- base::as.Date("1996-02-15")
ds_linear <-
Wats::county_month_birth_rate_2005_version |>
dplyr::filter(county_name == "oklahoma") |>
augment_year_data_with_month_resolution(date_name = "date")
h_spread <- function(scores) { quantile(x = scores, probs = c(.25, .75)) }
portfolio <- annotate_data(
ds_linear,
dv_name = "birth_rate",
center_function = median,
spread_function = h_spread
)
cartesian_rolling(
portfolio$ds_linear,
x_name = "date",
y_name = "birth_rate",
stage_id_name = "stage_id",
change_points = change_month,
change_point_labels = "Bombing Effect"
)