Package: rSPDE 2.5.2.9000

Overview | Asking for the compiled build | Toolchain prerequisites | Linux | macOS | Inspecting and adjusting the Makefile | Windows

Introduction | rSPDE sparse approximation | Benchmark setup | Results

Introduction | Implementation details | Setting up a data frame | Parameter estimation | rspde_lme implementation | inlabru Implementation | A spatial example | Fit with bounded_rho = FALSE | 1D Example with bounded_rho = FALSE | References

Introduction | Implementation details | Inlabru Implementation

Introduction | A fractional intrinsic model | Fitting the model with R-INLA | Extreme value models | An example with replicates | A more general model | Kriging with R-INLA implementation | Using intrinsic models without R-INLA | An example with estimated alpha and beta parameters

Introduction | Using the package to perform operator-based rational approximations | Constructing the approximation | A non-stationary model | Using the approximation | Spatial data and parameter estimation | References

Introduction | Covariance-based rational SPDE approach | Constructing the approximation | Using the approximation | Fitting a model | Kriging | Fitting a model with replicates | Spatial data and parameter estimation | Further details on rspde_lme | Fixing parameters | Setting starting values | Example: Fixing and setting starting values | Using a previous fit to initialize the optimization | An example with a non-stationary model | Simulating the data | Fitting the non-stationary rSPDE model | Fixing parameters in non-stationary models | Changing the type and the order of the rational approximation | References

Introduction | A toy data set | Fitting the model with R-INLA implementation of the rational SPDE approach | Kriging with R-INLA implementation of the rational SPDE approach | Fitting the model with inlabru implementation of the rational SPDE approach | Kriging with inlabru implementation of the rational SPDE approach | Fitting the model with rSPDE | Kriging with rSPDE | References

Introduction | Simulation | Inference | Kriging | Using the models in INLA | Using the models in inlabru | Kriging with the inlabru implementation | References

Introduction | An example with real data | An rSPDE model for precipitation | Examining the data | Creating the rSPDE model | Mesh | Setting up the data frame | Setting up the rSPDE model | Model fitting | inlabru results | inlabru results in the original scale | Predictions | An example with replicates | Simulating the data | Fitting the inlabru rSPDE model | An example with a non-stationary model | Comparing the results by cross-validation | Further options of the inlabru implementation | References

Introduction | Example with real data | An rSPDE model for precipitation | Examining the data | Creating the rSPDE model | Mesh | The observation matrix | Setting up the rSPDE model | The inla.stack | Model fitting | INLA results | rSPDE-INLA results | Predictions | An example with replicates | Simulating the data | Fitting the R-INLA rSPDE model | An example with a non-stationary model | Further options of the rSPDE-INLA implementation | Changing the upper bound for the smoothness parameter | Changing the order of the rational approximation | Estimating models with fixed smoothness | Estimating models with fixed smoothness and non-integer $\alpha$ | Estimating models with fixed smoothness and integer $\alpha$ | Changing the priors | Changing the priors of $\tau$ and $\kappa$ | Changing the priors of $\rho$ (range) and $\sigma$ (std. dev.) | Changing the prior of $\nu$ | Changing the starting values | Changing the type of the rational approximation | References