Pages that link to "Item:Q619127"

The following pages link to A general science-based framework for dynamical spatio-temporal models (Q619127):

Displaying 50 items.

• An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (Q68580) (← links)
• An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models (Q348513) (← links)
• Estimating parameters in delay differential equation models (Q484506) (← links)
• Inference for size demography from point pattern data using integral projection models (Q484721) (← links)
• Comments on: Inference for size demography from point process data using integral projection models (Q484726) (← links)
• Hierarchical Bayesian spatio-temporal Conway-Maxwell Poisson models with dynamic dispersion (Q486047) (← links)
• Computationally efficient statistical differential equation modeling using homogenization (Q486056) (← links)
• Ecological prediction with nonlinear multivariate time-frequency functional data models (Q486064) (← links)
• Rejoinder on: A general science-based framework for dynamical spatio-temporal models (Q619130) (← links)
• Advances and challenges in space-time modelling of natural events. Papers based on the presentations at the international spring school, Toledo, Spain, March 2010. (Q641161) (← links)
• A spatially varying stochastic differential equation model for animal movement (Q1624853) (← links)
• Reflected stochastic differential equation models for constrained animal movement (Q1680357) (← links)
• Bayesian non-parametric modeling for integro-difference equations (Q1702285) (← links)
• Temporal variation and scale in movement-based resource selection functions (Q1731181) (← links)
• Emulator-assisted reduced-rank ecological data assimilation for nonlinear multivariate dynamical spatio-temporal processes (Q1731188) (← links)
• Two-scale spatial models for binary data (Q1742839) (← links)
• A dynamic nonstationary spatio-temporal model for short term prediction of precipitation (Q1939996) (← links)
• A three-step local smoothing approach for estimating the mean and covariance functions of spatio-temporal data (Q2075448) (← links)
• Bayesian learning of stochastic dynamical models (Q2077593) (← links)
• A higher-order singular value decomposition tensor emulator for spatiotemporal simulators (Q2163486) (← links)
• Identification of distributed-parameter systems from sparse measurements (Q2294789) (← links)
• Comparison of deep neural networks and deep hierarchical models for spatio-temporal data (Q2419837) (← links)
• Covariance and precision matrix estimation for high-dimensional time series (Q2443210) (← links)
• Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes (Q2656594) (← links)
• Assessing the Impact of a Movement Network on the Spatiotemporal Spread of Infectious Diseases (Q4649048) (← links)
• Circuit Theory and Model-Based Inference for Landscape Connectivity (Q4916923) (← links)
• A Stationary Spatio‐Temporal GARCH Model (Q5111841) (← links)
• Predicting infectious disease outbreak risk via migratory waterfowl vectors (Q5128947) (← links)
• Polynomial nonlinear spatio‐temporal integro‐difference equation models (Q5495680) (← links)
• A Mechanistic Model of Annual Sulfate Concentrations in the United States (Q5881111) (← links)
• Modern statistical methods in oceanography: a hierarchical perspective (Q5965037) (← links)
• Extending the Gneiting class for modeling spatially isotropic and temporally symmetric vector random fields (Q6044189) (← links)
• Discussion of ``Saving storage in climate ensembles: a model-based stochastic approach'' (Q6050910) (← links)
• Covariate‐based cepstral parameterizations for time‐varying spatial error covariances (Q6090018) (← links)
• Physically motivated scale interaction parameterization in reduced rank quadratic nonlinear dynamic spatio‐temporal models (Q6090030) (← links)
• A Bayesian hierarchical model for forecasting intermountain snow dynamics (Q6090040) (← links)
• Latent multivariate log-gamma models for high-dimensional multitype responses with application to daily fine particulate matter and mortality counts (Q6104100) (← links)
• A Review of Data‐Driven Discovery for Dynamic Systems (Q6131430) (← links)
• Bayesian modeling of discrete-time point-referenced spatio-temporal data (Q6149602) (← links)
• Gaussian linear state‐space model for wind fields in the North‐East Atlantic (Q6179561) (← links)
• A model‐based approach for analog spatio‐temporal dynamic forecasting (Q6179615) (← links)
• An ensemble quadratic echo state network for non-linear spatio-temporal forecasting (Q6540526) (← links)
• A diffusion-based spatio-temporal extension of Gaussian Matérn fields (Q6583113) (← links)
• 30 years of space-time covariance functions (Q6602109) (← links)
• Sparsity in nonlinear dynamic spatiotemporal models using implied advection (Q6625866) (← links)
• Deep echo state networks with uncertainty quantification for spatio-temporal forecasting (Q6626063) (← links)
• Nonlinear reaction-diffusion process models improve inference for population dynamics (Q6626141) (← links)
• Improving piecewise linear snow density models through hierarchical spatial and orthogonal functional smoothing (Q6626481) (← links)
• Mechanistic spatial models for heavy metal pollution (Q6626513) (← links)
• Calibrated forecasts of quasi-periodic climate processes with deep echo state networks and penalized quantile regression (Q6626640) (← links)