Description Usage Arguments See Also Examples
View source: R/bandit_posterior.R
Generates a plot that shows the bandit posterior values as they are sequentially updated by the provided win / loss data.
1 2 3 4 5 | plot_bandit_posterior(
data,
prior = c(m1_good = 0.5, m2_good = 0.5),
win_probs = c(good = 1/2, bad = 1/3)
)
|
data |
data frame containing win loss data |
prior |
prior vector containing the probabilities of Machine 1 and Machine 2 being good, defaults to 50-50. |
win_probs |
vector containing the probabilities of winning on the good and bad machine respectively. |
bandit_sim
to generate data to use below
1 2 3 4 | # capture data from the `shiny` app `bandit_sim`.
data = data.frame(machine = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L),
outcome = c("W", "L", "W", "L", "L", "W", "L", "L", "L", "W"))
plot_bandit_posterior(data)
|
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