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Wats (version 1.0.1)

annotate_data: Finds midpoints and bands for the within and between cycles.

Description

Finds midpoints and bands for the within and between cycles. This the second of two functions that needs to be called to produce WATS Plots. AugmentZZZ is the first.

Usage

annotate_data(
  ds_linear,
  dv_name,
  center_function,
  spread_function,
  cycle_tally_name = "cycle_tally",
  stage_id_name = "stage_id",
  stage_progress_name = "stage_progress",
  proportion_through_cycle_name = "proportion_through_cycle",
  proportion_id_name = "proportion_id",
  terminal_point_in_cycle_name = "terminal_point_in_cycle"
)

Value

Returns a tibble::tibble() with additional variables. TODO: say what the variables are.

Arguments

ds_linear

The data.frame to containing the detailed data.

dv_name

The name of the dependent/criterion variable.

center_function

A function to calculate the center of a subsample.

spread_function

A function to calculate the bands of a subsample.

cycle_tally_name

The variable name indicating how many cycles have been completed.

stage_id_name

The variable name indicating the stage. In a typical interrupted time series, these values are "1" before the interruption and "2" after.

stage_progress_name

The variable name indicating the stage in a decimal form. This is mostly for internal uses.

proportion_through_cycle_name

The variable name indicating how far the point is through a cycle. For example, 0 degrees would be 0, 180 degrees would be 0.5, 359 degrees would be 0.9972, and 360 degrees would be 0.

proportion_id_name

The variable name indicating the ordinal position through a cycle.

terminal_point_in_cycle_name

The variable name indicating the last point within a given cycle.

Examples

Run this code
system.time({
library(Wats)
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 <- \(scores) { quantile(x = scores, probs = c(.25, .75)) }

portfolio <- annotate_data(
  ds_linear       = ds_linear,
  dv_name         = "birth_rate",
  center_function = median,
  spread_function = h_spread
)
portfolio$ds_stage_cycle
portfolio$ds_linear
portfolio$ds_periodic
})

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