Dirichlet adaptive shrinkage for compositional data
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Updated
Jan 19, 2018 - R
Dirichlet adaptive shrinkage for compositional data
R package for Dirichlet adaptive shrinkage and smoothing
Forecast mortality using Compositional Data Lee-Carter model - R Package
Implementation of Semantic Parsing with BERT and compositional pre-training on GeoQuery
Web applications for use with compositional data. Post-graduate work for Dr. Dot Dimuid and Prof. Timothy Olds at University of South Australia.
splineDensity Rpackage: Density estimation with smoothing B-spline
Stata module to examine dynamic compositional dependent variables
Replication of Frerebeau, N., Ben Amara, A. and Cantin, N. (2020)
Functional programming utilities for PHP
📦BEEM-Static: An R package for inferring microbial interactions based on Lotka-Volterra models
Simplex space operations for compositional data implemented in Python.
Deep learning for personalized interpretability for compositional health 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.
Practical introduction to modelling and testing for structural breaks in time-series data.
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.
Official repository for the 3DCoMPaT dataset (ECCV2022 Oral)
Longitudinal Latent Overall Toxicity (LOTox) profiles in osteosarcoma: a new taxonomy based on latent Markov models.
Forecasting the four-party vote share of the 20th presidential election of Republic of Korea
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