Spatial regression with non-parametric modeling of Fourier coefficients
From MaRDI portal
Publication:2151603
DOI10.1007/s42952-021-00156-yOpenAlexW3212001691MaRDI QIDQ2151603
Publication date: 5 July 2022
Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s42952-021-00156-y
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Nonparametric Bayesian models for a spatial covariance
- Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors
- Parameter estimation in high dimensional Gaussian distributions
- Properties of spatial cross-periodograms using fixed-domain asymptotics
- Improving the performance of predictive process modeling for large datasets
- Computational techniques for spatial logistic regression with large data sets
- A modeling approach for large spatial datasets
- Fixed-domain asymptotic properties of tapered maximum likelihood estimators
- Correlation theory of stationary and related random functions. Volume I: Basic results
- Interpolation of spatial data. Some theory for kriging
- Bayesian time series regression with nonparametric modeling of autocorrelation
- Nonparametric spectral methods for multivariate spatial and spatial-temporal data
- A case study competition among methods for analyzing large spatial data
- A Matrix-free Approach for Solving the Parametric Gaussian Process Maximum Likelihood Problem
- Multiresolution models for nonstationary spatial covariance functions
- Handbook of Spatial Statistics
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Bayesian Estimation of the Spectral Density of a Time Series
- Statistical Methods for Handling Incomplete Data
- Spectral density estimation for random fields via periodic embeddings
- A class of multi-resolution approximations for large spatial datasets
- Statistics for Spatial Data
- Approximate Likelihood for Large Irregularly Spaced Spatial Data
- An Algorithm for the Machine Calculation of Complex Fourier Series
- Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets
- Spatio‐temporal smoothing and EM estimation for massive remote‐sensing data sets
- Analyzing Nonstationary Spatial Data Using Piecewise Gaussian Processes
- ON STATIONARY PROCESSES IN THE PLANE
- Time Series
