Bayesian non-parametric modeling for integro-difference equations
From MaRDI portal
Publication:1702285
DOI10.1007/s11222-016-9719-1zbMath1384.62299OpenAlexW2560092605MaRDI QIDQ1702285
Robert Richardson, Athanasios Kottas, Bruno Sansó
Publication date: 28 February 2018
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11222-016-9719-1
Hermite polynomialsDirichlet process mixturesHamiltonian Markov chain Monte Carlospatial Dirichlet process
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A general science-based framework for dynamical spatio-temporal models
- Bayesian forecasting and dynamic models.
- Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds
- Nonstationary covariance functions that model space--time interactions.
- Flexible integro-difference equation modeling for spatio-temporal data
- Inference from iterative simulation using multiple sequences
- Dispersal and pattern formation in a discrete-time predator-prey model
- Stationary space-time Gaussian fields and their time autoregressive representation
- MODELS FOR TWO-DIMENSIONAL STATIONARY STOCHASTIC PROCESSES
- A kernel-based spectral model for non-Gaussian spatio-temporal processes
- DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
- Blur-generated non-separable space–time models
- Classes of Nonseparable, Spatio-Temporal Stationary Covariance Functions
- Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
- A dimension-reduced approach to space-time Kalman filtering
- Modeling Disease Incidence Data with Spatial and Spatio Temporal Dirichlet Process Mixtures
- Statistics for Spatial Data
- Polynomial nonlinear spatio‐temporal integro‐difference equation models
- Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing
- A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities
This page was built for publication: Bayesian non-parametric modeling for integro-difference equations