Preprocessing of centred logratio transformed density functions using smoothing splines

DOI10.1080/02664763.2015.1103706OpenAlexW2263497564MaRDI QIDQ5138088

Jitka Machalová, Karel Hron, Gianna S. Monti

Publication date: 3 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1501.07047

zbMATH Keywords

smoothing splineBayes spaces\(B\)-spline representationcentred logratio transformation

Mathematics Subject Classification ID

Multivariate analysis (62H99) Numerical computation using splines (65D07) Numerical smoothing, curve fitting (65D10)

Related Items (5)

Compositional regression with functional response ⋮ Bivariate densities in Bayes spaces: orthogonal decomposition and spline representation ⋮ Compositional splines for representation of density functions ⋮ Compositional scalar-on-function regression with application to sediment particle size distributions ⋮ Logratio Approach to Distributional Modeling

Uses Software

• fBasics
• fda (R)
• FITPACK
• RMetrics

Cites Work

• Bayes spaces: use of improper distributions and exponential families
• Dimensionality reduction when data are density functions
• A practical guide to splines
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Smoothing spline density estimation: Theory
• Functional data analysis.
• Hilbert space of probability density functions based on Aitchison geometry
• A general method for the construction of interpolating or smoothing spline-functions
• Bayes Hilbert Spaces
• Symbolic Data Analysis
• Density estimation via hybrid splines
• Far beyond the classical data models: symbolic data analysis
• Bayesian-multiplicative treatment of count zeros in compositional data sets
• Smoothing Spline Density Estimation: A Dimensionless Automatic Algorithm
• An algorithm for data smoothing using spline functions
• Computation of Smoothing and Interpolating Natural Splines via Local Bases
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