present_k_values_bs: Present calculated k values with bootstrapped confidence...

In pernille267/commutability.selectivity: Commutability and non-selectivity evaluation tools

Present calculated k values with bootstrapped confidence interval for all unique measurement system comparisons

Description

Present calculated k values with bootstrapped confidence interval for all unique measurement system comparisons

Usage

present_k_values_bs(
  data,
  groups = "Comparison",
  LFDT = FALSE,
  decimals = 6,
  n = 100,
  level = 0.95,
  seed_id = 1,
  two_sided = FALSE
)

Arguments

data	A data frame or data table with format LFDT or WFDT (default) enclosed with all replicated measurements
groups	Character vector - The names of the grouping columns of the data. Default is 'Comparison'
LFDT	Logical - Is data of format LDFT or WFDT (default)?
decimals	Integer - how many decimals should be used in the output data table. Default is 6
n	The number of bootstrap resamples of k values for each group. Note that choosing a large number may result in a significant computation time. n > 500 is not recommended!
level	A numeric value that captures the overall confidence level of bootstrapped confidence intervals
seed_id	Integer - Set a unique seed for reproducibility, or generate a random integer based on a distribution
two_sided	Logical - should two-sided confidence intervals be calculated. Default is no because of the practical use of k

Value

A data table with n rows and 2 columns, where n is the number of unique measurement system combinations in data

Examples

present_k_values_bs(data = sampled_cs_measurements, n = 10, level = 0.99, seed_id = 5, two_sided = TRUE)

pernille267/commutability.selectivity documentation built on July 20, 2022, 9:11 a.m.