Spatio-temporal expanding distance asymptotic framework for locally stationary processes
From MaRDI portal
Publication:2082342
DOI10.1007/s13171-020-00213-4OpenAlexW3081806455MaRDI QIDQ2082342
Jialuo Liu, Tingjin Chu, Haonan Wang, Jun Zhu
Publication date: 4 October 2022
Published in: Sankhyā. Series A (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13171-020-00213-4
spatial statisticsrandom fieldsnonstationary processescovariance functionsspatio-temporal statistics
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- High dimensional stochastic regression with latent factors, endogeneity and nonlinearity
- Local intrinsic stationarity and its inference
- Penalized maximum likelihood estimation and variable selection in geostatistics
- Nonparametric regression for locally stationary time series
- Local linear quantile estimation for nonstationary time series
- Gaussian maximum likelihood estimation for ARMA models. II: Spatial processes
- Uniform asymptotic normality of the maximum likelihood estimator
- Interpolation of spatial data. Some theory for kriging
- Maximum likelihood estimation of parameters under a spatial sampling scheme
- Properties of nonparametric estimators of autocovariance for stationary random fields
- Fitting time series models to nonstationary processes
- Nonlinear time series. Nonparametric and parametric methods
- The asymptotic distribution of REML estimators
- Fixed-domain asymptotics for a subclass of Matérn-type Gaussian random fields
- A likelihood ratio test for separability of covariances
- Testing for separability of spatial\,-\,temporal covariance functions
- Static and roving sensor data fusion for spatio-temporal hazard mapping with application to occupational exposure assessment
- A Spectral Domain Test for Stationarity of Spatio‐Temporal Data
- Likelihood Approximations for Big Nonstationary Spatial Temporal Lattice Data
- Maximum likelihood estimation of models for residual covariance in spatial regression
- Handbook of Spatial Statistics
- Spatial Statistics and Spatio‐Temporal Data
- Nonseparable, Stationary Covariance Functions for Space–Time Data
- Classes of Nonseparable, Spatio-Temporal Stationary Covariance Functions
- Spectral methods for nonstationary spatial processes
- Mission CO2ntrol: A Statistical Scientist's Role in Remote Sensing of Atmospheric Carbon Dioxide
- Nonparametric Estimation of Probability Density Functions for Irregularly Observed Spatial Data
- A Test for Stationarity for Irregularly Spaced Spatial Data
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- Space–Time Covariance Functions
- Modeling Temporally Evolving and Spatially Globally Dependent Data
This page was built for publication: Spatio-temporal expanding distance asymptotic framework for locally stationary processes
