Bayes spaces: use of improper distributions and exponential families

DOI10.1007/s13398-012-0082-6zbMath1280.62030OpenAlexW2147940467WikidataQ60182766 ScholiaQ60182766MaRDI QIDQ380445

M. I. Ortego, Raimon Tolosana-Delgado, Karl Gerald van den Boogaart, Juan José Egozcue, Vera Pawlowsky-Glahn

Publication date: 14 November 2013

Published in: Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A: Matemáticas. RACSAM (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13398-012-0082-6

zbMATH Keywords

sensitivityderivativessimplexAitchison geometry

Mathematics Subject Classification ID

Bayesian inference (62F15) Foundations and philosophical topics in statistics (62A01)

Related Items (10)

Differential models for evolutionary compositions ⋮ Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation ⋮ A Regression Model for Compositional Data Based on the Shifted-Dirichlet Distribution ⋮ Nonparametric Estimation of Repeated Densities with Heterogeneous Sample Sizes ⋮ Preprocessing of centred logratio transformed density functions using smoothing splines ⋮ Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics ⋮ Simplicial principal component analysis for density functions in Bayes spaces ⋮ Compositional data: the sample space and its structure ⋮ A Class-Kriging predictor for functional compositions with application to particle-size curves in heterogeneous aquifers ⋮ Bayes Hilbert Spaces

Cites Work

• Reply to letter to the editor by S. Rehder and U. Zier on ``Logratio analysis and compositional distance
• Hilbert space of probability density functions based on Aitchison geometry
• On the Foundations of Statistical Inference
• Principal component analysis of compositional data
• The multivariate skew-normal distribution
• Statistical Interpretation of Species Composition
• On criteria for measures of compositional difference
• Geometric approach to statistical analysis on the simplex
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