brownianMuSd

sample_list <- list(rnorm(1000, 0, 1))
mean_vec <- c(mean(sample_list[[1]]))
sd_vec <- c(sd(sample_list[[1]]))
chains <- tibble::tibble(chain = rep,
                         mean_value = NA,
                         sd_value = NA)
for (i in 2:100000) {
  sample_list[[i]] <- rnorm(1000, mean_vec[i - 1], sd_vec[i - 1])
  mean_vec[i] <- mean(sample_list[[i]])
  sd_vec[i] <- sd(sample_list[[i]])
}