parabar - Progress Bar for Parallel Tasks
A simple interface in the form of R6 classes for executing tasks in parallel, tracking their progress, and displaying accurate progress bars.
Last updated
parallel-computingprogress-bar
7.67 score 22 stars 8 dependents 25 scripts 3.5k downloadspowerly - Sample Size Analysis for Psychological Networks and More
An implementation of the sample size computation method for network models proposed by Constantin et al. (2023) <doi:10.1037/met0000555>. The implementation takes the form of a three-step recursive algorithm designed to find an optimal sample size given a model specification and a performance measure of interest. It starts with a Monte Carlo simulation step for computing the performance measure and a statistic at various sample sizes selected from an initial sample size range. It continues with a monotone curve-fitting step for interpolating the statistic across the entire sample size range. The final step employs stratified bootstrapping to quantify the uncertainty around the fitted curve.
Last updated
network-modelspower-analysispsychologysample-size-calculation
4.00 score 10 stars 3 scripts 248 downloads
doParabar - 'foreach' Parallel Adapter for 'parabar' Backends
Provides a 'foreach' parallel adapter for 'parabar' backends. This package offers a minimal implementation of the '%dopar%' operator, enabling users to run 'foreach' loops in parallel, leveraging the parallel and progress-tracking capabilities of the 'parabar' package. Learn more about 'parabar' and 'doParabar' at <https://parabar.mihaiconstantin.com>.
Last updated
foreachparallel-computing
3.18 score 1 stars 1 dependents 6 scripts 165 downloads