Simulate a Bayesian Bandit choice for a given set of probabilities and a number of points

Usage

ov_simulate_setter_distribution(
  dvw,
  play_phase = c("Reception", "Transition"),
  n_sim = 500,
  priors = list(name = "beta", par1 = 1, par2 = 1),
  epsilon = 1,
  filter_sim = FALSE,
  attack_options = "use_data",
  setter_position_by = "rotation",
  history_table = NULL,
  attack_by = "code",
  exclude_attacks = c("PR"),
  rotation = "SHM",
  shiny_progress = NULL
)

Arguments

dvw: string or datavolley: a datavolley object as returned by datavolley::dv_read() or a path to datavolley file
play_phase: character: one or both of "Reception", "Transition"
n_sim: integer: number of simulations
priors: numeric: prior distribution of the kill rate for the different attacking options
epsilon: numeric: reward size
filter_sim: logical:
attack_options: string: either "use_data" or "use_history"
setter_position_by: string: either "rotation" or "front_back"
history_table: list: (only if attack_options is "use_history") the object returned by ov_create_history_table()
attack_by: string: either "code", "zone", "tempo", "setter call", "attacker_name", "player_role"
exclude_attacks: character: vector of attack codes to exclude
rotation: string: (only relevant when attack_by is "player_role") either "SHM" (assume a setter-hitter-middle rotation order), or "SMH" (setter-middle-hitter)
shiny_progress: numeric: an optional two-element vector. If not NULL or NA, shiny::setProgress() calls will be made during simulation with values in this range

Examples

dvw <- ovdata_example("190301_kats_beds")
system.time({
  ssd <- ov_simulate_setter_distribution(dvw = dvw, play_phase = "Reception",
                                         n_sim = 100, attack_by = "setter call",
                                         setter_position_by = "front_back")
})
#>    user  system elapsed 
#>   5.070   0.048   5.076

Simulate a Bayesian Bandit choice for a given set of probabilities and a number of points

Usage

Arguments

See also

Examples