se_param {CAISEr}  R Documentation 
Calculates the standard errors of a given statistic using parametric formulas
se_param(Xk, dif = "simple", comparisons = "all.vs.all", ...)
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

Data frame containing, for each pair of interest, the estimated difference (column "Phi") and the sample standard error (column "SE")
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):305338, 2019.
Felipe Campelo (fcampelo@ufmg.br, f.campelo@aston.ac.uk)
# 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")