View source: R/annotate-data.R
annotate_data | R Documentation |
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.
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"
)
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 |
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. |
Returns a tibble::tibble()
with additional variables.
TODO: say what the variables are.
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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