There are 2 repositories under compositional-data topic.
Network construction, analysis, and comparison for microbial compositional data
Inference of microbial interaction networks from large-scale heterogeneous abundance data
Compositional data analysis in Julia
Official repository for the 3DCoMPaT dataset (ECCV2022 Oral)
Implementation of Semantic Parsing with BERT and compositional pre-training on GeoQuery
📦BEEM-Static: An R package for inferring microbial interactions based on Lotka-Volterra models
Imputation of zeros, nondetects and missing data in compositional data sets
Sourcing Archaeological Materials by Chemical Composition - :exclamation: This is a read-only mirror from https://codeberg.org/tesselle/nexus
Hopefully taking out the complexity of using the simplex: functions to generate, manipulate and plot data on the simplex
Practical introduction to modelling and testing for structural breaks in time-series data.
Archive: Data, scripts, and outputs for the paper "Sparse Estimation of Correlations among Microbiomes (SECOM)". Please check our ANCOMBC R package for the most up-to-date SECOM functions.
R package for estimating sparse and positive definite basis covariance matrices from compositional data
Biomedicine Data Science and Biostatistics - UCM bio2ds-ucm · they/them This is the Github repo of the Biomedicine Data Science and Biostatistics research group at Complutense University
CompSign: An R package for differential abundance of compositional mutational signatures
Forecasting the four-party vote share of the 20th presidential election of Republic of Korea
Presidential election data set from South Korea
Stata module to examine dynamic compositional dependent variables
About me: mathematician, PhD Stats, Assistant Professor and scicomm
splineDensity Rpackage: Density estimation with smoothing B-spline
Web applications for use with compositional data. Post-graduate work for Dr. Dot Dimuid and Prof. Timothy Olds at University of South Australia.
Longitudinal Latent Overall Toxicity (LOTox) profiles in osteosarcoma: a new taxonomy based on latent Markov models.
Replication of Frerebeau, N., Ben Amara, A. and Cantin, N. (2020)
CRAN Task View: Compositional Data Analysis
Using champion mastery data from Rot games API to visualize champion connections based on correlation metrics of compositional data in a network. Unsupervised learning was also used to categorize the champions. Lastly, weighted graph distance was used to make a recommender system for new champions based on played chamoions input.