mc_sdwdnsp1: Simulate several data sets with different non-selectivity...

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

Simulate several data sets with different non-selectivity profiles defined by setting 1 using parallel computation

Description

Performance; 100 - TT 2 sec TF 2 sec FT 0.25 sec FF 0.15 sec, 1,000 - TT 3.9 sec TF 2.3 sec FT 2.1 sec FF 1.7 sec, 10,000 TT 8.1 sec TF 6 sec FT 18 sec FF 17.5 sec

Usage

mc_sdwdnsp1(
  parameter_row = c(1),
  m = 100,
  n = "r",
  R = "r",
  cv_vec = "r",
  ci = "r",
  mmax = 2.5,
  p = 0.05,
  parallel = TRUE,
  progress_bar = TRUE
)

Arguments

parameter_row	A data frame or data table with only 1 row. Should contain a subset of simulation parameters. Parameters that may be included are n, R, cvx, cvy, ci_lwr, ci_upr, mmax and p
m	Integer - The number of data sets to be simulated
n	Integer or 'r' - number of unique samples
R	Integer or 'r' - Number of unique replicated measurements on each sample
cv_vec	Vector with two elements or 'r' - MS CVs in decimal
ci	Vector with two elements or 'r' - Concentration interval
mmax	A number signifying the maximum multiple of relocation of clinical samples affected by differences in selectivity
p	A number signifying the average proportion of clinical samples to be relocated
parallel	should we allow parallelization to be performed
progress_bar	should a progress bar be displayed. Default is TRUE

Details

parallel should only be TRUE used if parameter_row has few rows, or else it will be faster to just use standard sapply() by setting parallel to FALSE. the latter is true if subsets of rows are simulated in parallel. This function is not available for other users than Windows.

Value

A list of simulated data tables with 4 columns, where two of which are measurement results from two MSs in comparison having differences in selectivity profiles. In addition, n * R rows

Examples

mc_sdwdnsp1(m = 100, parallel = FALSE, progress_bar = TRUE)

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