calc_se {CAISEr} | R Documentation |
Calculates the sample standard error for the estimator differences between multiple algorithms on a given instance.
calc_se( Xk, dif = "simple", comparisons = "all.vs.all", method = "param", boot.R = 999 )
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 |
method |
method used to calculate the interval. Accepts "param" (using parametric formulas based on normality of the sampling distribution of the means) or "boot" (for bootstrap). |
boot.R |
(optional) number of bootstrap resamples
(if |
If dif == "perc"
it returns the standard errors for the sample
estimates of pairs
(mu2 - mu1) / mu, where mu1, mu2 are the means of the
populations that generated sample vectors x1, x2, and
If dif == "simple"
it returns the SE for sample estimator of
(mu2 - mu1)
a list object containing the following items:
Phi.est
- estimated values of the statistic of interest for
each pair of algorithms of interest (all pairs if comparisons == "all.vs.all"
,
or all pairs containing the first algorithm if comparisons == "all.vs.first"
).
se
- standard error estimates
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.
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(50, 15, 5)) # mean = 15, sd = 3 calc_se(Xk, dif = "simple", comparisons = "all.vs.all", method = "param") calc_se(Xk, dif = "simple", comparisons = "all.vs.all", method = "boot") calc_se(Xk, dif = "perc", comparisons = "all.vs.first", method = "param") calc_se(Xk, dif = "perc", comparisons = "all.vs.first", method = "boot") calc_se(Xk, dif = "perc", comparisons = "all.vs.all", method = "param") calc_se(Xk, dif = "perc", comparisons = "all.vs.all", method = "boot")