Exploring spatial nonlinearity using additive approximation
From MaRDI portal
Publication:2465273
DOI10.3150/07-BEJ5093zbMath1127.62087arXiv0708.4132MaRDI QIDQ2465273
Qiwei Yao, Arvid Lundervold, Dag Tjøstheim, Zu-di Lu
Publication date: 9 January 2008
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0708.4132
asymptotic normalityuniform convergencemagnetic resonance images\(\alpha\)-mixingspatial modelsbackfittingadditive approximationnonparametric kernel estimationauto-normal specificationuniform convergence rates for regression estimation
Inference from spatial processes (62M30) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)
Related Items
Functional-coefficient spatial autoregressive models with nonparametric spatial weights, B-spline estimation for semiparametric varying-coefficient partially linear regression with spatial data, Adaptively Varying-Coefficient Spatiotemporal Models, Local linear spatial quantile regression, Robust estimation for spatial semiparametric varying coefficient partially linear regression, Asymptotic distribution of local medians, Frequency polygons for continuous random fields, Discussion of: ``Models as approximations, Inference on power law spatial trends, Asymptotic spectral theory for spatial data, Semi-parametric regression: efficiency gains from modeling the nonparametric part, On a Semiparametric Data‐Driven Nonlinear Model with Penalized Spatio‐Temporal Lag Interactions, Rejoinder, Estimating spatial quantile regression with functional coefficients: a robust semiparametric framework, Statistical analysis of a spatio-temporal model with location-dependent parameters and a test for spatial stationarity, Variable selection for spatial semivarying coefficient models, Moment inequalities for spatial processes, B-spline estimation for spatial data, Estimation in semiparametric spatial regression, Oracally efficient spline smoothing of nonlinear additive autoregression models with simultaneous confidence band, Nonparametric estimation of noisy integral equations of the second kind, The nonparametric estimation of long memory spatio-temporal random field models, Asymptotic theory for nonparametric regression with spatial data, Nonparametric Estimation of Probability Density Functions for Irregularly Observed Spatial Data, Semiparametric likelihood estimation in survival models with informative censoring, B-spline estimation for varying coefficient regression with spatial data
Cites Work
- The existence and asymptotic properties of a backfitting projection algorithm under weak conditions
- A simple smooth backfitting method for additive models
- On the central limit theorem for stationary mixing random fields
- Mixing: Properties and examples
- Kernel density estimation for spatial processes: The \(L_{1}\) theory
- Direct estimation of low-dimensional components in additive models.
- Local linear spatial regression
- Estimation in semiparametric spatial regression
- Bandwidth selection for smooth backfitting in additive models
- A Kernel Method for Smoothing Point Process Data
- Equivalence of Smoothing Parameter Selectors in Density and Intensity Estimation
- Nonparametric Identification of Nonlinear Time Series: Projections
- Kernel density estimation for random fields: TheL1Theory
- Smooth Backfitting in Practice
- A kernel method of estimating structured nonparametric regression based on marginal integration
- ON STATIONARY PROCESSES IN THE PLANE
- Density estimation for spatial linear processes
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item