ip_fit_sl: Iterative proportional fitting to scale seed values to...
In ryantimpe/ipfitr: Iterative Proportion Fitting for the Tidyverse

Iterative proportional fitting to scale seed values to multiple target subtotals.

ip_fit_sl(datatable, targets, assumptions,
  datatable.value.name = "value", target.value.names = "value",
  assumption.value.names = c("value", "value_min", "value_max"),
  assumption.drop.names = c("Notes"), max.error = 0.01,
  max.iterations = 25, minmax.smash.param = 1/3, save.tars = FALSE,
  show.messages = TRUE)

`datatable`	A data frame of values to be scaled to targets.
`targets`	A list of data frames containing subtotal targets for the `datatable`. All totals in each target should be equal.
`assumptions`	A single data frame containing data belonging to `freeze_cells`, `freeze_slice`, `minmax_cells`, and `minmax_slice`.
`target.value.names`	The names of the series in `targets` containing subtotals to scale. Can be string or array of strings.
`assumption.value.names`	The names of the series in `assumptions` containing subtotals to scale. Three item array of the freeze value name, min value, max value.
`assumption.drop.names`	The names of the series in `assumptions` to exclude from analysis. Usually columns containing notes.
`max.error`	The maximum total absolute difference allowed between final scaled values and targets. Iterative scaling will complete once the error is below this threshold or `max.iterations` occur.
`max.iterations`	The maximum number of iterations of scaling. Iterative scaling with end once this value is reached, even if the error is above `max.error`.
`minmax.smash.param`	Numeric value of 0 < x < 1. Following an out-of-bounds occurence for `minmax_cells`, the `minmax.smash.param` is the additional value added to the scaled value to bring it back into bounds. Values close to 0 bind the value to the violated bound, while close to 1 bind the value to the other bound. Values closer to 0 will require more iterations to complete.
`datatable.value.names`	The name of the series in `datatable` containing the values to be scaled.

A dataframe with the same dimensionality as datatable, with all values scaled to the subtotals specified in each data frame in targets and meeting criteria supplied in assumptions.

ryantimpe/ipfitr documentation built on May 14, 2019, 8:55 a.m.