Cointegrated linear processes in Bayes Hilbert space

DOI10.1016/j.spl.2018.11.032zbMath1450.62115OpenAlexW2904727216WikidataQ128752495 ScholiaQ128752495MaRDI QIDQ1726899

Won-Ki Seo, Brendan K. Beare

Publication date: 20 February 2019

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2018.11.032

zbMATH Keywords

cointegrationfunctional dataBayes Hilbert space

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional data analysis (62R10) Probability theory on linear topological spaces (60B11)

Related Items (5)

Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation ⋮ Bivariate densities in Bayes spaces: orthogonal decomposition and spline representation ⋮ INFERENCE ON THE DIMENSION OF THE NONSTATIONARY SUBSPACE IN FUNCTIONAL TIME SERIES ⋮ REPRESENTATION OF I(1) AND I(2) AUTOREGRESSIVE HILBERTIAN PROCESSES ⋮ COINTEGRATION IN FUNCTIONAL AUTOREGRESSIVE PROCESSES

Cites Work

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• Simplicial principal component analysis for density functions in Bayes spaces
• Dimensionality reduction when data are density functions
• Functional regression of continuous state distributions
• Local likelihood density estimation
• Hilbert space of probability density functions based on Aitchison geometry
• Bayes Hilbert Spaces
• Inference for Density Families Using Functional Principal Component Analysis
• A family of minimax rates for density estimators in continuous time
• Cointegrated Linear Processes in Hilbert Space
• Functional data analysis for density functions by transformation to a Hilbert space
• Nonstationarity in time series of state densities

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