Spatial variation of total column ozone on a global scale
From MaRDI portal
Publication:995742
DOI10.1214/07-AOAS106zbMath1129.62115arXiv0709.0394MaRDI QIDQ995742
Publication date: 10 September 2007
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0709.0394
Applications of statistics to environmental and related topics (62P12) Meteorology and atmospheric physics (86A10)
Related Items
Excursion probability of Gaussian random fields on sphere, Parameter-related projection-based iterative algorithm for a kind of generalized positive semidefinite least squares problem, Reflecting time-Space Gaussian random field on compact Riemannian manifold and excursion probability, A statistical modeling approach for air quality data based on physical dispersion processes and its application to ozone modeling, Non-stationary Cross-Covariance Models for Multivariate Processes on a Globe, A multi-resolution model for non-Gaussian random fields on a sphere with application to ionospheric electrostatic potentials, Reducing storage of global wind ensembles with stochastic generators, Spatial Matérn Fields Driven by Non-Gaussian Noise, Comment, Modeling nonstationary covariance function with convolution on sphere, Data generation for axially symmetric processes on the sphere, Notes on spherical bifractional Brownian motion, Multi-scale shotgun stochastic search for large spatial datasets, Global space-time models for climate ensembles, Nonparametric Bayesian modelling of longitudinally integrated covariance functions on spheres, Modeling Temporally Evolving and Spatially Globally Dependent Data, Fast simulation for Gaussian random fields on compact Riemannian manifolds, Estimating intensity functions of spatial inhomogeneous Poisson point processes via a Stein estimator, Nonparametric Bayesian modeling and estimation of spatial correlation functions for global data, Approximate Bayesian inference for large spatial datasets using predictive process models, Spherical process models for global spatial statistics, A simplified representation of the covariance structure of axially symmetric processes on the sphere, Stochastic approximation of score functions for Gaussian processes, Intrinsic random functions on the sphere, Fractional stochastic partial differential equation for random tangent fields on the sphere, Spectral analysis of fractional hyperbolic diffusion equations with random data, Needlet approximation for isotropic random fields on the sphere, Reduced-rank spatio-temporal modeling of air pollution concentrations in the multi-ethnic study of atherosclerosis and air pollution, Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping, Improving crop model inference through Bayesian melding with spatially varying parameters, Some theory for anisotropic processes on the sphere, Hierarchical spatial models for predicting tree species assemblages across large domains, Time varying axially symmetric vector random fields on the sphere, Nonstationary covariance models for global data, Multivariate isotropic random fields on spheres: nonparametric Bayesian modeling and \(L^p\) fast approximations, Gaussian Predictive Process Models for Large Spatial Data Sets, A modeling approach for large spatial datasets, Covariance functions on spheres cross time: beyond spatial isotropy and temporal stationarity, Extremes of spherical fractional Brownian motion, Bayesian inference for brain activity from functional magnetic resonance imaging collected at two spatial resolutions, Modeling Tangential Vector Fields on a Sphere