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Let's separate simulation from summary. #2

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Let's separate simulation from summary. #2

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27 changes: 19 additions & 8 deletions R/experimentr.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
#' @param prior_a length two numeric - (alpha, beta) prior beliefs of each conversion rate
#' @param prior_b numberic - (alpha, beta) prior beliefs of each conversion rate
#'
#' @return belief of chances group a better at each peek
#' @return a set of experiments from two treatments
#' @export
#'
#' @examples
Expand All @@ -24,16 +24,27 @@ perform_experiment <- function(entrants, a_conv, b_conv,
# see the formula for posterior hyperparameters.
mutate(group_a_conv_rate_beliefs = map2(cumsum(group_a), 1:n(),
function(x, y) {
rbeta(1e3, x + prior_a[[1]], y - x + prior_b[[2]])
rbeta(1e3, x + prior_a[[1]] + 1, y - x + prior_b[[2]] + 1)
})) %>%
mutate(group_b_conv_rate_beliefs = map2(cumsum(group_b), 1:n(),
function(x, y) {
rbeta(1e3, x + prior_b[[1]], y - x + prior_b[[2]])
})) %>%
mutate(belief_a_better = map2_dbl(group_a_conv_rate_beliefs, group_b_conv_rate_beliefs,
function(x, y) {
mean(x > y)
})) %>%
rbeta(1e3, x + prior_b[[1]] + 1, y - x + prior_b[[2]] + 1)
}))
}

#' Using posterior beliefs, ask and answer the belief we should have that A has a higher conversion rate.
#'
#' @param .experiments
#'
#' @return belief of chances group a better at each peek
#' @export
#'
#' @examples
beliefs_a_is_better <- function(.experiments) {
.experiments %>%
mutate(belief_a_better = map2_dbl(
group_a_conv_rate_beliefs, group_b_conv_rate_beliefs,
function(x, y) { mean(x > y) })) %>%
pull(belief_a_better) -> beliefs_a_better

beliefs_a_better[
Expand Down