cartesian_rolling: Linear Plot with Rolling Summaries
In OuhscBbmc/Wats: Wrap Around Time Series Graphics

View source: R/cartesian-rolling.R

cartesian_rolling

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 `stage_id` is "1", and is "2" afterwards.
`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 `stage_id` value. If no vector is specified, a default will be chosen, based on the number of stages.
`palette_light`	A vector of colors used for the light graphical elements. The vector should have one color for each `stage_id` value. If no vector is specified, a default will be chosen, based on the number of stages.
`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 `rolling_center_name`.
`draw_rolling_band`	A boolean value indicating if a band should be plotted that envelopes the rolling estimates (whose values are take from the `rolling_lower_name` and `rolling_upper_name`.
`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"
)

OuhscBbmc/Wats documentation built on April 22, 2024, 10:32 p.m.