"Call:"
"RoBTT(x1 = x1, x2 = x2, prior_delta = prior(\"cauchy\", list(0, "
"    1/sqrt(2)), list(0, Inf)), prior_rho = prior(\"beta\", list(3, "
"    3)), prior_nu = prior(\"exp\", list(1)), prior_delta_null = prior(\"normal\", "
"    list(0, 0.15), list(0, Inf)), likelihood = c(\"normal\", \"t\"), "
"    parallel = FALSE, seed = 1)"
""
"Robust Bayesian t-test"
"Diagnostics overview:"
" Model Distribution       Prior delta        Prior rho    Prior nu    max[error(MCMC)] max[error(MCMC)/SD] min(ESS) max(R-hat)"
"     1       normal Normal(0, 0.15)[0, Inf] Spike(0.5)                         0.09314               0.011     8534      1.001"
"     2            t Normal(0, 0.15)[0, Inf] Spike(0.5) Exponential(1)          2.28632               0.014     5299      1.000"
"     3       normal Normal(0, 0.15)[0, Inf] Beta(3, 3)                         0.08714               0.010     9624      1.000"
"     4            t Normal(0, 0.15)[0, Inf] Beta(3, 3) Exponential(1)          4.20340               0.015     4489      1.001"
"     5       normal Cauchy(0, 0.71)[0, Inf] Spike(0.5)                         0.08626               0.011     8354      1.000"
"     6            t Cauchy(0, 0.71)[0, Inf] Spike(0.5) Exponential(1)          1.38443               0.015     4648      1.001"
"     7       normal Cauchy(0, 0.71)[0, Inf] Beta(3, 3)                         0.07285               0.010    10360      1.000"
"     8            t Cauchy(0, 0.71)[0, Inf] Beta(3, 3) Exponential(1)          2.34447               0.014     4856      1.000"
"[0;31mModel (4): There were 1 divergent transitions.[0m"
