Vectorize Example

example.R

library(microbenchmark)
library(purrr)
library(tibble)

num_sims <- 1000

lambda <- 0.15
mu <- 7
sigma <- 2

non_vectorized_simulation <- function(num_sims) {
    losses <- vector(mode = "list", length = num_sims)
    num_claims <- rpois(num_sims, lambda = lambda)
    for (i in seq_len(num_sims)) {
        losses[[i]] <- rlnorm(num_claims[i], meanlog = mu, sdlog = sigma)
    }
    
    purrr::map_dfr(losses, ~ tibble::tibble(loss = .x), .id = "simyear")
}

vectorized_simulation <- function(num_sims) {
    num_claims <- rpois(num_sims, lambda = lambda)
    losses <- rlnorm(sum(num_claims), meanlog = mu, sdlog = sigma)
    simyear <- seq_len(num_sims)
    has_losses <- num_claims > 0
    years_with_losses <- simyear[has_losses]
    num_losses <- num_claims[has_losses]
    year_idx <- seq_along(num_losses)
    
    purrr::map2_dfr(year_idx, num_losses, 
                    ~ tibble::tibble(simyear = years_with_losses[.x],
                             loss = losses[.x + (seq_len(.y) - 1)]))
    
}

results <- microbenchmark::microbenchmark(
    nonvec = non_vectorized_simulation(50000),
    vec = vectorized_simulation(50000),
    times = 10
    
)

print(results)