RHybrid: Rhybrid

# library(hybridpower)
# SEED <- 1234
#
# # Case 1: independent samples t-test example
# set.seed(SEED)
# x_classical <- hp_ttest$new(
#   ns = seq(10, 90, 10),
#   design = 'two.sample',
#   d = 0.5
# )
# x_classical$classical_power()
#
# # Bayesian-classical hybrid power
# set.seed(SEED)
# x_hybrid <- hp_ttest$new(
#   ns = seq(10, 90, 10),
#   design = 'two.sample',
#   n_prior = 1000,
#   prior = 'normal',
#   prior_mu = .5,
#   prior_sigma = .1
# )
# x_hybrid$hybrid_power()
# x_hybrid$assurance()
# x_hybrid$power_quantiles()
# x_hybrid$boxplot()
#
# # Both can be calculated using a single instance
# set.seed(SEED)
# x_both <- hp_ttest$new(
#   ns = seq(10, 90, 10),
#   d = .5,
#   design = 'two.sample',
#   n_prior = 1000,
#   prior = 'normal',
#   prior_mu = .5,
#   prior_sigma = .1,
#   assurance_level_props = c(.5, .8),
#   quantiles = c(0, .2, .5, .7, 1)
# )
# x_both$hybrid_power()
# x_both$assurance()
# x_both$power_quantiles()
# x_both$boxplot()
# x_both$assurance_level()
#
# ## Case 2: sign test example
# set.seed(SEED)
# x_classical <- hp_sign$new(
#   ns = seq(50, 150, 10),
#   p_0 = 0.5,
#   p_1 = 0.3
# )
# x_classical$classical_power()
#
# set.seed(SEED)
# x_hybrid <- hp_sign$new(
#   parallel=T,
#   ns = seq(50, 150, 10),
#   p_0 = .5,
#   prior = 'uniform',
#   prior_lower = .2,
#   prior_upper = .4,
#   n_prior = 5000
# )
# x_hybrid$hybrid_power()
# x_hybrid$assurance()
# x_hybrid$boxplot()
#
# # Case 3: Welch ANOVA example
# set.seed(SEED)
# x_classical_welch <- hp_oneway_anova$new(
#   ns = seq(40, 120, 20),
#   mu = c(2, 2.5, 2.2),
#   sigma = c(1.0, 1.1, 1.2),
#   design = 'fe',
#   n_MC=1000
# )
# x_classical_welch$classical_power()
#
# set.seed(SEED)
# x_hybrid_welch <- hp_oneway_anova$new(
#   ns = seq(40, 120, 20),
#   prior_mu = c(2.0, 2.5, 2.2),
#   prior_sigma = c(.1, .2, .15),
#   sigma = c(1.0, 1.1, 1.2),
#   design = 'fe',
#   prior = 'normal',
#   n_prior = 1000,
#   n_MC = 1000
# )
# x_hybrid_welch$hybrid_power()
# x_hybrid_welch$assurance()
# x_hybrid_welch$boxplot()