Enhanced Implementation of MissForest Algorithm
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Updated
May 15, 2020 - R
Enhanced Implementation of MissForest Algorithm
A set of R scripts to process the BFAST algorithm in various points and with parallelization
Raw files for a document covering techniques for speeding up R, especially before parallelization.
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
Set of functions to semi-automatically build and test Ordinary Least Squares (OLS) models in R in parallel.
R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.
Tracking the progress of mc*apply with progress bar.
π R package future.callr: A Future API for Parallel Processing using 'callr'
π R package: future.apply - Apply Function to Elements in Parallel using Futures
π R package: future: Unified Parallel and Distributed Processing in R for Everyone
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