Bayesian estimation in a high dimensional parameter framework

DOI10.1214/14-EJS935zbMath1297.62188MaRDI QIDQ457965

Denis Bosq, María D. Ruiz-Medina

Publication date: 30 September 2014

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

Full work available at URL: https://projecteuclid.org/euclid.ejs/1410181226

zbMATH Keywords

asymptotic relative efficiencyBayesian estimationHilbert valued Gaussian random variableHilbert valued Poisson process

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10)

Related Items (3)

Spatial Cox processes in an infinite-dimensional framework ⋮ Log-Gaussian Cox processes in infinite-dimensional spaces ⋮ Dynamical multiple regression in function spaces, under kernel regressors, with ARH(1) errors

Uses Software

• fda (R)
• BayesX

Cites Work

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• Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs
• Robust functional principal components: a projection-pursuit approach
• Spatial autoregressive and moving average Hilbertian processes
• Wavelet methods for continuous-time prediction using Hilbert-valued autoregressive processes
• Linear processes in function spaces. Theory and applications
• Exponential bounds for intensity of jumps
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Approximation spline de la prevision d'un processus fonctionnel autorégressif d'ordre 1
• Inference and Prediction in Large Dimensions

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