30 Years of space–time covariance functions
… constructing new classes of space–time covariance functions. … of parametric classes of
space–time covariance functions. An … We introduce some classes of continuous functions, defined …
space–time covariance functions. An … We introduce some classes of continuous functions, defined …
Flexible spatial covariance functions
AM Schmidt, P Guttorp - Spatial Statistics, 2020 - Elsevier
… In the last decade, other flexible covariate dependent covariance structures have been … by
assuming a spatio-temporal framework, wherein the temporal and spatial structures are jointly …
assuming a spatio-temporal framework, wherein the temporal and spatial structures are jointly …
Non-parametric Bayesian covariate-dependent multivariate functional clustering: An application to time-series data for multiple air pollutants
… In Section 3.1, we evaluate the methods in covariate-dependent trivariate functional
clustering. In Section 3.2, we assess the methods in covariate-dependent time-varying bivariate …
clustering. In Section 3.2, we assess the methods in covariate-dependent time-varying bivariate …
[PDF][PDF] Lagrangian Spatio-Temporal Covariance Functions for Multivariate Nonstationary Random Fields
MLO Salvaña - 2021 - repository.kaust.edu.sa
… provide a suite of covariance function models that are capable … to develop a class of
spatio-temporal covariance functions for … Covariate-dependent spatio-temporal covariance …
spatio-temporal covariance functions for … Covariate-dependent spatio-temporal covariance …
Incorporating covariate information in the covariance structure of misaligned spatial data
E Yarali, F Rivaz - Environmetrics, 2020 - Wiley Online Library
… new class of covariate-dependent nonstationary covariance … on modeling two large
spatio-temporal processes where the … exponential and wave covariance functions for vector b with …
spatio-temporal processes where the … exponential and wave covariance functions for vector b with …
A Bayesian multivariate model with temporal dependence on random partition of areal data
J Pavani, FA Quintana - arXiv preprint arXiv:2401.08303, 2024 - arxiv.org
… (2013), developed a mixture model where spatial and temporal effects are introduced by
using space-time covariate dependent kernel stick-breaking processes. Then, this modeling …
using space-time covariate dependent kernel stick-breaking processes. Then, this modeling …
A nonstationary spatial covariance model for data on graphs
MF Christensen, PD Hoff - arXiv preprint arXiv:2207.10513, 2022 - arxiv.org
… In particular, we highlight a class … and anisotropic spatial covariance via the use of a complex
covariance function or kernel, our model uses a relatively simple covariance function, and …
covariance function or kernel, our model uses a relatively simple covariance function, and …
A new estimation in functional linear concurrent model with covariate dependent and noise contamination
H Ding, M Yao, R Zhang - Metrika, 2023 - Springer
… the consistent estimator of the covariance function \(C_X(t,s)\), … to be independent and
the covariance function \(C_e(t,s)\) was … structure, the estimator of covariance function of \(C_X(t,s)\) …
the covariance function \(C_e(t,s)\) was … structure, the estimator of covariance function of \(C_X(t,s)\) …
Spatio-temporal stick-breaking process
C Grazian - Bayesian Analysis, 2024 - projecteuclid.org
… First, we derive the covariance function conditionally on the beta variables Vk, the knots ψk
… use a spatiotemporal covariance function defined as the product of one covariance function …
… use a spatiotemporal covariance function defined as the product of one covariance function …
Extending the Gneiting class for modeling spatially isotropic and temporally symmetric vector random fields
… multivariate space-time covariance functions that allow to have different spatial and temporal
… and multivariate Gneiting-type classes of nonseparable space-time covariances. Section 4 …
… and multivariate Gneiting-type classes of nonseparable space-time covariances. Section 4 …