Spatial autoregressive and moving average Hilbertian processes

DOI10.1016/j.jmva.2010.09.005zbMath1327.62266OpenAlexW2083870405MaRDI QIDQ618154

María D. Ruiz-Medina

Publication date: 14 January 2011

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2010.09.005

zbMATH Keywords

spatial functional statisticsspatial Hilbert-valued processestensorial product of Hilbert-valued processestwo-parameter Markov processestwo-parameter martingale differences

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Numerical computation using splines (65D07) Applications of statistics to environmental and related topics (62P12) Economic models of real-world systems (e.g., electricity markets, etc.) (91B74) Spatial models in economics (91B72) Linear operators in reproducing-kernel Hilbert spaces (including de Branges, de Branges-Rovnyak, and other structured spaces) (47B32)

Related Items (17)

Spatial Cox processes in an infinite-dimensional framework ⋮ A functional-data approach to the Argo data ⋮ Macroscaling Limit Theorems for Filtered Spatiotemporal Random Fields ⋮ Heterogeneous Spatial Dynamical Regression in a Hilbert-Valued Context ⋮ Spatial functional normal mixed effect approach for curve classification ⋮ Hilbertian spatial periodically correlated first order autoregressive models ⋮ On estimation and prediction in spatial functional linear regression model ⋮ Nonparametric Prediction for Spatial Dependent Functional Data Under Fixed Sampling Design ⋮ Estimation of functional ARMA models ⋮ Computing functional estimators of spatiotemporal long-range dependence parameters in the spectral-wavelet domain ⋮ Bayesian estimation in a high dimensional parameter framework ⋮ Asymptotic properties of a component-wise ARH(1) plug-in predictor ⋮ Functional analysis of variance for Hilbert-valued multivariate fixed effect models ⋮ Dynamical multiple regression in function spaces, under kernel regressors, with ARH(1) errors ⋮ Recent developments in complex and spatially correlated functional data ⋮ Maximum-likelihood asymptotic inference for autoregressive Hilbertian processes ⋮ Least-squares estimation of multifractional random fields in a Hilbert-valued context

Uses Software

• fda (R)

Cites Work

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