The progressify package allows you to easily add progress
reporting to sequential and parallel map-reduce code by piping to the
progressify() function. Easy!
library(progressify)
handlers(global = TRUE)
library(boot)
# Run bootstrap with progress signaling
x <- 1:100
my_stat <- function(data, i) mean(data[i])
res <- boot(data = x, statistic = my_stat, R = 1000) |> progressify()
This vignette demonstrates how to use this approach to add progress
reporting to boot functions such as boot(), censboot(), and tsboot().
The boot package provides functions for generating bootstrap replicates. Because these computations are iterative and computationally intensive, they can benefit significantly from progress reporting.
For example, boot() runs a statistic function R times:
library(boot)
x <- 1:100
my_stat <- function(data, i) mean(data[i])
res <- boot(data = x, statistic = my_stat, R = 1000)
By default, boot() provides no feedback on how far it has progressed.
However, we can easily add progress reporting using the progressify() function:
library(boot)
library(progressify)
handlers(global = TRUE)
x <- 1:100
my_stat <- function(data, i) mean(data[i])
res <- boot(data = x, statistic = my_stat, R = 1000) |> progressify()
The progressify() function supports the following boot
functions:
boot()censboot()tsboot()
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