se_param {CAISEr} | R Documentation |
Parametric standard errors
Description
Calculates the standard errors of a given statistic using parametric formulas
Usage
se_param(Xk, dif = "simple", comparisons = "all.vs.all", ...)
Arguments
Xk |
list object where each position contains a vector of observations of algorithm k on a given problem instance. |
dif |
name of the difference for which the SEs are desired. Accepts "perc" (for percent differences) or "simple" (for simple differences) |
comparisons |
standard errors to be calculated. Accepts "all.vs.first"
(in which cases the first object in |
... |
other parameters (used only for compatibility with calls to
|
Value
Data frame containing, for each pair of interest, the estimated difference (column "Phi") and the sample standard error (column "SE")
References
E.C. Fieller: Some problems in interval estimation. Journal of the Royal Statistical Society. Series B (Methodological) 16(2), 175–185 (1954)
V. Franz: Ratios: A short guide to confidence limits and proper use (2007). https://arxiv.org/pdf/0710.2024v1.pdf
D.C. Montgomery, C.G. Runger: Applied Statistics and Probability for Engineers, 6th ed. Wiley (2013)
F. Campelo, F. Takahashi: Sample size estimation for power and accuracy in the experimental comparison of algorithms. Journal of Heuristics 25(2):305-338, 2019.
Author(s)
Felipe Campelo (fcampelo@ufmg.br, f.campelo@aston.ac.uk)
Examples
# three vectors of normally distributed observations
set.seed(1234)
Xk <- list(rnorm(10, 5, 1), # mean = 5, sd = 1,
rnorm(20, 10, 2), # mean = 10, sd = 2,
rnorm(20, 15, 5)) # mean = 15, sd = 3
se_param(Xk, dif = "simple", comparisons = "all.vs.all")
se_param(Xk, dif = "perc", comparisons = "all.vs.first")
se_param(Xk, dif = "perc", comparisons = "all.vs.all")