Bayesian-multiplicative treatment of count zeros in compositional data sets

DOI10.1177/1471082X14535524OpenAlexW2163169537WikidataQ58002986 ScholiaQ58002986MaRDI QIDQ4971410

Karel Hron, Josep Antoni Martín-Fernández, Peter Filzmoser, Javier Palarea Palarea-Albaladejo, Matthias Templ

Publication date: 12 October 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x14535524

zbMATH Keywords

Dirichlet distributionposterior estimatelog-ratio transformationsdiscrete compositionzero replacement

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (11)

Compositional regression with functional response ⋮ Three approaches to supervised learning for compositional data with pairwise logratios ⋮ Bivariate densities in Bayes spaces: orthogonal decomposition and spline representation ⋮ A Zero-Inflated Logistic Normal Multinomial Model for Extracting Microbial Compositions ⋮ A flexible quasi‐likelihood model for microbiome abundance count data ⋮ Preprocessing of centred logratio transformed density functions using smoothing splines ⋮ When relative and absolute information matter: Compositional predictor with a total in generalized linear models ⋮ Compositional splines for representation of density functions ⋮ A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes ⋮ A comparison of generalised linear models and compositional models for ordered categorical data ⋮ Partial linear regression of compositional data

Uses Software

• R
• robCompositions

Cites Work

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