🚀 R package: future: Unified Parallel and Distributed Processing in R for Everyone
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Updated
Jun 30, 2024 - R
🚀 R package: future: Unified Parallel and Distributed Processing in R for Everyone
🚀 R package: future.apply - Apply Function to Elements in Parallel using Futures
Tracking the progress of mc*apply with progress bar.
R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.
A set of R scripts to process the BFAST algorithm in various points and with parallelization
🚀 R package future.callr: A Future API for Parallel Processing using 'callr'
Small model to simulate biomass production on a global scale. Products are Gross Primary Production (GPP), Net Primary Production (NPP). It is based on a modified version of the Farquhar approach (Haxeltine and Prentice 1996, Farquhar et al. 1980). Where possible, it uses vectorization and parallelization and dynamically downloads latest av
Enhanced Implementation of MissForest Algorithm
Raw files for a document covering techniques for speeding up R, especially before parallelization.
Set of functions to semi-automatically build and test Ordinary Least Squares (OLS) models in R in parallel.
Multicore and utility functions for Seurat 2 & 3, using doMC / foreach packages.
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