Density estimation in an infinite dimensional space: Application to diffusion processes

DOI10.1016/S1631-073X(02)02247-1zbMath0999.62028OpenAlexW1983676558MaRDI QIDQ1598490

Sophie Dabo-Niang

Publication date: 3 December 2002

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s1631-073x(02)02247-1

zbMATH Keywords

rate of convergencediffusion processinfinite-dimensional space

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Markov processes: estimation; hidden Markov models (62M05)

Related Items (13)

Nonparametric density estimation for intentionally corrupted functional data ⋮ Defining probability density for a distribution of random functions ⋮ Unnamed Item ⋮ Modèle à indice fonctionnel simple. (Single functional index model) ⋮ Lower bound in regression for functional data by representation of small ball probabilities ⋮ Single and multiple index functional regression models with nonparametric link ⋮ Mixture inner product spaces and their application to functional data analysis ⋮ Curves discrimination: a nonparametric functional approach ⋮ Convergence of \(k\) nearest neighbor kernel estimator in nonparametric functional regression ⋮ Kernel density estimator in an infinite-dimensional space with a rate of convergence in the case of diffusion process. ⋮ Kernel regression estimation in a Banach space ⋮ Note on conditional mode estimation for functional dependent data ⋮ Kernel regression estimation when the regressor takes values in metric space

Uses Software

• fda (R)

Cites Work

• Functional data analysis
• Linear processes in function spaces. Theory and applications
• Transformations of Wiener integrals under translations
• Density estimation by orthogonal series in an infinite dimensional space: Application to processes of diffusion type I
• Dimension fractale et estimation de la régression dans des espaces vectoriels semi-normés

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