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https://github.com/aariq/pca-vs-pls

Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."

https://github.com/aariq/pca-vs-pls

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
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    Academic publication links
    Links to: zenodo.org
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (9.6%) to scientific vocabulary

Keywords

multivariate-analysis multivariate-data multivariate-regression multivariate-statistics partial-least-squares-regression pca pca-analysis pls-da plsr-model principal-component-analysis principal-components-regression
Last synced: 6 months ago · JSON representation

Repository

Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."

Basic Info
  • Host: GitHub
  • Owner: Aariq
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 310 MB
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
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Topics
multivariate-analysis multivariate-data multivariate-regression multivariate-statistics partial-least-squares-regression pca pca-analysis pls-da plsr-model principal-component-analysis principal-components-regression
Created over 7 years ago · Last pushed almost 5 years ago
Metadata Files
Readme

README.md

Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."

DOI

Research compendium for Scott ER, Crone EE (2021) Using the right tool for the job: the difference between unsupervised and supervised analyses of multivariate ecological data. Oecologia. https://doi.org/10.1007/s00442-020-04848-w

This repository contains the R scripts (.R and .Rmd files) necessary to reproduce results from this paper. Datasets generated by these scripts are found in the "data" directory. To run scripts "1-muir-data-wrangling.R" and "2-muir-analys.Rmd", you will need to download the dataset from Muir et al (2017), from Data Dryad. Unzip the download and place the contents inside "data/muir/". Figures and tables generated by the analysis are found in the "out" directory.

This project uses renv to manage package dependencies. After downloading this (or forking it via GitHub), open the .Rproj file. After installing and loading the renv package, simply run restore() to install the exact configuration of R packages originally used in this analysis.

References

Muir CD, Conesa MÀ, Roldán EJ, et al (2017) Weak coordination between leaf structure and function among closely related tomato species. New Phytol 213:1642–1653. doi: 10.1111/nph.14285

Owner

  • Name: Eric R. Scott
  • Login: Aariq
  • Kind: user
  • Company: University of Arizona, @cct-datascience

Scientific Programmer & Educator at University of Arizona

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