output_summary {countts}

Summarize the simulation results and generate the regret plot

Description

Summarize the simulation results and generate the regret plot

Usage

output_summary(
  S = 30,
  num_cov = 4,
  T.init = 20,
  T0 = 1000,
  alpha = 1,
  gam = 25,
  K = 20,
  dist_env = c("Negative Binomial", "Poisson", "Linear TS", "ZIP", "ZINB"),
  show_figure = TRUE
)

Arguments

S

number of replicates of the experiment (greater than 1). Default is 30.

num_cov

dimension for beta and gamma; we assume that they have the same dimensions for now. Default is 4.

T.init

length of the initial exploration stage. Default is 20.

T0

number of decision times. Default is 1000.

alpha

tuning parameter that controls the exploration-exploitation tradeoff. Default is 1.

gam

over dispersion level of the environment model; this is only useful when the environment model is negative binomial or zero-inflated negative binomial. Default is 25.

K

number of actions/intervention options. Default is 20.

dist_env

tuning parameter that controls which environment model to use, with the options "Negative Binomial", "Poisson", "Linear TS", "ZIP", "ZINB"

show_figure

A logical flag specifying that the regret plot of the model should be returned if true (default), otherwise, false.

Value

The summary of the simulation results with cumulative regret, regret, and parameters is generated along with the optional output of the regret plot (show_figure = TRUE).

References

• Liu, X., Deliu, N., Chakraborty, T., Bell, L., & Chakraborty, B. (2023). Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study. arXiv preprint arXiv:2311.14359. https://arxiv.org/abs/2311.14359

Examples

output_summary(S = 2, num_cov = 2, T.init = 3, T0 = 5, dist_env = "Negative Binomial")