acc_end_digits: Extension of acc_shape_or_scale to examine uniform...

View source: R/acc_end_digits.R

acc_end_digitsR Documentation

Extension of acc_shape_or_scale to examine uniform distributions of end digits

Description

This implementation contrasts the empirical distribution of a measurement variables against assumed distributions. The approach is adapted from the idea of rootograms (Tukey (1977)) which is also applicable for count data (Kleiber and Zeileis (2016)).

Usage

acc_end_digits(resp_vars = NULL, study_data, meta_data, label_col = VAR_NAMES)

Arguments

resp_vars

variable the names of the measurement variables, mandatory

study_data

data.frame the data frame that contains the measurements

meta_data

data.frame the data frame that contains metadata attributes of study data

label_col

variable attribute the name of the column in the metadata with labels of variables

Value

a list with:

  • SummaryData: data frame underlying the plot

  • SummaryPlot: ggplot2 distribution plot comparing expected with observed distribution

ALGORITHM OF THIS IMPLEMENTATION:

  • This implementation is restricted to data of type float or integer.

  • Missing codes are removed from resp_vars (if defined in the metadata)

  • The user must specify the column of the metadata containing probability distribution (currently only: normal, uniform, gamma)

  • Parameters of each distribution can be estimated from the data or are specified by the user

  • A histogram-like plot contrasts the empirical vs. the technical distribution

See Also

Online Documentation


dataquieR documentation built on Aug. 31, 2022, 5:08 p.m.