A semiparametric model for compositional data analysis in presence of covariates on the simplex.

DOI10.1007/BF02595709zbMath1039.62032OpenAlexW2047618536MaRDI QIDQ1872864

Malini Iyengar, Dey, Dipak K.

Publication date: 18 May 2003

Published in: Test (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02595709

zbMATH Keywords

Markov chain Monte Carloposterior predictive distributionsemiparametric density estimation

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Density estimation (62G07)

Related Items (1)

Flexible non-parametric regression models for compositional data

Cites Work

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• Multivariate Liouville distributions
• Some parametric models on the simplex
• Multivariate Liouville distributions. III
• Estimating the dimension of a model
• On the existence and uniqueness of the maximum likelihood estimates for certain generalized linear models
• Dynamic modelling and penalized likelihood estimation for discrete time survival data
• Dependence Properties of Generalized Liouville Distributions on the Simplex
• Bayesian Analysis of Proportional Hazards Models Built from Monotone Functions
• Semiparametric Bayesian Analysis of Survival Data
• Monte Carlo sampling methods using Markov chains and their applications

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