compositional-data

There are 30 repositories under compositional-data topic.

  • stefpeschel/NetCoMi

    Network construction, analysis, and comparison for microbial compositional data

    Language:R157712628

  • meringlab/FlashWeave.jl

    Inference of microbial interaction networks from large-scale heterogeneous abundance data

    Language:Julia757408

  • JuliaEarth/CoDa.jl

    Compositional data analysis in Julia

    Language:Julia60798

  • boehm-s/fun-php

    Functional programming utilities for PHP

    Language:PHP31212

  • Vision-CAIR/3DCoMPaT

    Official repository for the 3DCoMPaT dataset (ECCV2022 Oral)

    Language:Jupyter Notebook16311

  • ofgulban/compoda

    Simplex space operations for compositional data implemented in Python.

    Language:Python13610

  • simhag/Compositional-Pre-Training-for-Semantic-Parsing-with-BERT

    Implementation of Semantic Parsing with BERT and compositional pre-training on GeoQuery

    Language:Scala11005

  • lch14forever/beem-static

    📦BEEM-Static: An R package for inferring microbial interactions based on Lotka-Volterra models

    Language:R9528

  • mcomas/codapack

    Language:Java9613

  • Japal/zCompositions

    Imputation of zeros, nondetects and missing data in compositional data sets

    Language:R7171

  • mpascariu/CoDa

    Forecast mortality using Compositional Data Lee-Carter model - R Package

    Language:R7302

  • nphdang/DeepCoDA

    Deep learning for personalized interpretability for compositional health data

    Language:Python6311
  • nexus

    tesselle/nexus

    :globe_with_meridians: Sourcing Archaeological Materials by Chemical Composition

    Language:R5250

  • tystan/simplexity

    Hopefully taking out the complexity of using the simplex: functions to generate, manipulate and plot data on the simplex

    Language:R4100

  • avisionh/analysis-structuralbreak

    Practical introduction to modelling and testing for structural breaks in time-series data.

    2101

  • FrederickHuangLin/SECOM-Code-Archive

    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.

    Language:HTML2100

  • ajmolstad/SpPDCC

    R package for estimating sparse and positive definite basis covariance matrices from compositional data

    Language:R1101

  • bio2ds-ucm/bio2ds-ucm

    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

    Language:R1303

  • kkdey/dash

    Dirichlet adaptive shrinkage for compositional data

    Language:R1201

  • kkdey/dashr

    R package for Dirichlet adaptive shrinkage and smoothing

    Language:R1202

  • seungwoo-stat/20th-PE-forecast

    Forecasting the four-party vote share of the 20th presidential election of Republic of Korea

    Language:R1111

  • andyphilips/dynsimpie

    Stata module to examine dynamic compositional dependent variables

    Language:Stata0200

  • dadosdelaplace/dadosdelaplace

    About me: mathematician, PhD Stats, Assistant Professor and scicomm

    01013

  • fpavone/pacs_spline_density

    splineDensity Rpackage: Density estimation with smoothing B-spline

    Language:C++0000

  • jhhughes256/comp_app

    Web applications for use with compositional data. Post-graduate work for Dr. Dot Dimuid and Prof. Timothy Olds at University of South Australia.

    Language:R0250

  • lm687/CompSign

    CompSign: An R package for differential abundance of compositional mutational signatures

    Language:R0220

  • mspreafico/BO06-LOTox

    Longitudinal Latent Overall Toxicity (LOTox) profiles in osteosarcoma: a new taxonomy based on latent Markov models.

    Language:R0100

  • seungwoo-stat/south-korea-election

    Presidential election data set from South Korea

    Language:R0100

  • nfrerebeau/TaphoCeram

    Replication of Frerebeau, N., Ben Amara, A. and Cantin, N. (2020)

    Language:TeX20

  • SamGalanakis/SimilarSummonersGraph

    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.

    Language:HTML10