🚀 R package: future: Unified Parallel and Distributed Processing in R for Everyone
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Updated
May 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
🚀 R package future.callr: A Future API for Parallel Processing using 'callr'
Tracking the progress of mc*apply with progress bar.
R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.
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.
Parallel simulation with mrgsolve and futures
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
Raw files for a document covering techniques for speeding up R, especially before parallelization.
Enhanced Implementation of MissForest Algorithm
A set of R scripts to process the BFAST algorithm in various points and with parallelization
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