## All functions

TSP.dist()

TSP instance generator (for testing/examples)

boot_sdm()

Bootstrap the sampling distribution of the mean

calc_instances()

Calculates number of instances for the comparison of multiple algorithms

calc_nreps()

Determine sample sizes for a set of algorithms on a single problem instance

calc_se()

Calculates the standard error for simple and percent differences

consolidate_partial_results()

Consolidate results from partial files

dummyalgo()

Dummy algorithm routine to test the sampling procedures

dummyinstance()

Dummy instance routine to test the sampling procedures

example_SANN()

Simulated annealing (for testing/examples)

get_observations()

Run an algorithm on a problem.

plot(<CAISEr>)

plot.CAISEr

plot(<nreps>)

plot.nreps

print(<CAISEr>)

print.CAISEr

run_experiment()

Run a full experiment for comparing multiple algorithms using multiple instances

se_boot()

Bootstrap standard errors

se_param()

Parametric standard errors

summary(<CAISEr>)

summary.CAISEr

summary(<nreps>)

summary.nreps