README.md

In krisrs1128/MSLF: Package accompanying "Bootstrap Confidence Regions for Learned Feature Embeddings"

LFBCR

This repository contains the data and code for the preprint online here:

Sankaran, Kris, (2022). Bootstrap Confidence Regions for Learned Feature Embeddings. Accessed 30 Jan 2022. Online at https://arxiv.org/abs/2102.10388

How to cite

Please cite this compendium as:

Sankaran, Kris, (2022). Compendium of R code and data for Bootstrap Confidence Regions for Learned Feature Embeddings. Accessed 30 Jan 2022. Online at https://github.com/krisrs1128/LFBCR

Contents

The analysis directory contains:

• :file_folder: data: Instructions for downloading data used in this analysis.
• :file_folder: figures: Plots and other illustrations.
• :file_folder: simulations: Notebooks for running the low-rank and spatial point process simulations.
• :file_folder: data_analysis: Notebooks for running the spatial proteomics application.

How to run in your browser or download and run locally

This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need installed on your computer the R software itself and optionally RStudio Desktop.

You can download the compendium as a zip from from this URL: master.zip. After unzipping: - open the .Rproj file in RStudio - run devtools::install() to ensure you have the packages this analysis depends on (also listed in the DESCRIPTION file).

Licenses

Text and figures : CC-BY-4.0

Code : See the DESCRIPTION file

Data : CC-0 attribution requested in reuse

Contributions

We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

krisrs1128/MSLF documentation built on March 21, 2023, 10:21 a.m.