##### On a simulated example, with 1 sample (gaussianity test):
list.comp <- list(f1 = "norm", g1 = "norm")
list.param <- list(f1 = list(mean = 0, sd = 1), g1 = list(mean = 2, sd = 0.7))
## Simulate data:
sim1 <- rsimmix(n = 300, unknownComp_weight = 0.85, comp.dist = list(list.comp$f1,list.comp$g1),
comp.param = list(list.param$f1, list.param$g1))$mixt.data
## Perform the test hypothesis:
list.comp <- list(f1 = NULL, g1 = "norm")
list.param <- list(f1 = NULL, g1 = list(mean = 2, sd = 0.7))
gaussTest <- admix_test(samples = list(sim1), sym.f = TRUE, test.method = 'Poly', sim_U = NULL,
n_sim_tab = 50, comp.dist = list.comp, comp.param = list.param,
support = "Real", conf.level = 0.95, parallel = FALSE, n_cpu = 2)
print(gaussTest)
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