Package index • rSPDE

rSPDE package

rSPDE rSPDE-package: Rational approximations of fractional SPDEs.

rSPDE models

rspde.matern(): Matern rSPDE model object for INLA

rspde.metric_graph(): Matern rSPDE model object for metric graphs in INLA

rspde.spacetime(): Space-Time Random Fields via SPDE Approximation

matern.operators(): Rational approximations of stationary Gaussian Matern random fields

matern2d.operators(): Rational approximations of stationary anisotropic Gaussian Matern random fields

spde.matern.operators(): Rational approximations of non-stationary Gaussian SPDE Matern random fields

fractional.operators(): Rational approximations of fractional operators

matern.rational(): Rational approximation of the Matern fields on intervals and metric graphs

spacetime.operators(): Space-time random fields

Linear mixed-effects models

rspde_lme(): rSPDE linear mixed effects models

predict(<rspde_lme>): Prediction of a mixed effects regression model on a metric graph.

summary(<rspde_lme>): Summary Method for rspde_lme Objects.

glance(<rspde_lme>): Glance at an rspde_lme object

augment(<rspde_lme>): Augment data with information from a rspde_lme object

Intrinsic models

intrinsic.matern.operators(): Covariance-based approximations of intrinsic fields

variogram.intrinsic.spde(): Variogram of intrinsic SPDE model

rspde.intrinsic.matern(): Intrinsic Matern rSPDE model object for INLA

simulate(<intrinsicCBrSPDEobj>): Simulation of a fractional intrinsic SPDE using the covariance-based rational SPDE approximation

Log-likelihood

rSPDE.matern.loglike(): Object-based log-likelihood function for latent Gaussian fractional SPDE model using the rational approximations

rSPDE.loglike(): Object-based log-likelihood function for latent Gaussian fractional SPDE model

spde.matern.loglike(): Parameter-based log-likelihood for a latent Gaussian Matern SPDE model using a rational SPDE approximation

rSPDE.construct.matern.loglike(): Constructor of Matern loglikelihood functions.

construct.spde.matern.loglike(): Constructor of Matern loglikelihood functions for non-stationary models.

Computation of precision matrices

rspde.matern.precision(): Precision matrix of the covariance-based rational approximation of stationary Gaussian Matern random fields

rspde.matern.precision.integer(): Precision matrix of stationary Gaussian Matern random fields with integer covariance exponent

Methods for rSPDE, CBrSPDE and spacetime objects

predict(<rSPDEobj>): Prediction of a fractional SPDE using a rational SPDE approximation

simulate(<rSPDEobj>): Simulation of a fractional SPDE using a rational SPDE approximation

summary(<rSPDEobj>) print(<summary.rSPDEobj>) print(<rSPDEobj>): Summarise rSPDE objects

update(<rSPDEobj>): Update parameters of rSPDEobj objects

predict(<CBrSPDEobj>): Prediction of a fractional SPDE using the covariance-based rational SPDE approximation

simulate(<CBrSPDEobj>): Simulation of a fractional SPDE using the covariance-based rational SPDE approximation

summary(<CBrSPDEobj>) print(<summary.CBrSPDEobj>) print(<CBrSPDEobj>): Summarise CBrSPDE objects

update(<CBrSPDEobj>): Update parameters of CBrSPDEobj objects

precision(): Get the precision matrix of CBrSPDEobj objects

predict(<CBrSPDEobj2d>): Prediction of an anisotropic Whittle-Matern field

simulate(<CBrSPDEobj2d>): Simulation of a fractional SPDE using the covariance-based rational SPDE approximation

summary(<CBrSPDEobj2d>) print(<summary.CBrSPDEobj2d>) print(<CBrSPDEobj2d>): Summarise CBrSPDEobj2d objects

update(<CBrSPDEobj2d>): Update parameters of CBrSPDEobj2d objects

precision(<CBrSPDEobj2d>): Get the precision matrix of CBrSPDEobj2d objects

simulate(<rSPDEobj1d>): Simulation of a Matern field using a rational SPDE approximation

summary(<rSPDEobj1d>) print(<summary.rSPDEobj1d>) print(<rSPDEobj1d>): Summarise rSPDE objects without FEM

update(<rSPDEobj1d>): Update parameters of rSPDEobj1d objects

precision(<rSPDEobj1d>): Get the precision matrix of rSPDEobj1d objects

precision(<spacetimeobj>): Get the precision matrix of spacetimeobj objects

predict(<spacetimeobj>): Prediction of a space-time SPDE

simulate(<spacetimeobj>): Simulation of space-time models

update.spacetimeobj(): Update space-time operator object with new parameters

summary(<spacetimeobj>) print(<summary.spacetimeobj>) print(<spacetimeobj>): Summarise spacetime objects

Functions and methods for R-INLA rSPDE objects

rspde.make.A(): Observation/prediction matrices for rSPDE models.

spde.make.A(): Observation/prediction matrices for rSPDE models with integer smoothness.

rspde.make.index(): rSPDE model index vector generation

graph_data_rspde(): Data extraction from metric graphs for 'rSPDE' models

rspde.mesh.project() rspde.mesh.projector(): Calculate a lattice projection to/from an inla.mesh for rSPDE objects

rspde.result(): rSPDE result extraction from INLA estimation results

summary(<rspde_result>): Summary for posteriors of field parameters for an inla_rspde model from a rspde_result object

precision(<inla_rspde>): Get the precision matrix of inla_rspde objects

gg_df(): Data frame for result objects from R-INLA fitted models to be used in ggplot2

gg_df(<rspde_result>): Data frame for rspde_result objects to be used in ggplot2

Functions and methods for rSPDE interface for inlabru

cross_validation(): Perform cross-validation on a list of fitted models.

group_predict(): Perform prediction on a testing set based on a training set

bru_get_mapper.inla_rspde() ibm_n.bru_mapper_inla_rspde() ibm_values.bru_mapper_inla_rspde() ibm_jacobian.bru_mapper_inla_rspde(): rSPDE inlabru mapper

bru_get_mapper.inla_rspde_spacetime(): rSPDE space time inlabru mapper

rSPDE.A1d(): Observation matrix for finite element discretization on R

rSPDE.fem1d(): Finite element calculations for problems on R

rSPDE.fem2d(): Finite element calculations for problems in 2D

rSPDE.Ast(): Observation matrix for space-time models

Auxiliary functions

create_train_test_indices(): Create train and test splits to be used in the cross_validation function

get.initial.values.rSPDE(): Initial values for log-likelihood optimization in rSPDE models with a latent stationary Gaussian Matern model

require.nowarnings(): Warnings free loading of add-on packages

matern.covariance(): The Matern covariance function

matern.rational.cov(): Rational approximation of the Matern covariance

folded.matern.covariance.1d(): The 1d folded Matern covariance function

folded.matern.covariance.2d(): The 2d folded Matern covariance function

rspde.matern.precision.opt(): Optimized precision matrix of the covariance-based rational approximation

rspde.matern.precision.integer.opt(): Optimized precision matrix of stationary Gaussian Matern random fields with integer covariance exponent

`rational.order<-`(): Changing the order of the rational approximation

`rational.type<-`(): Changing the type of the rational approximation

rational.order(): Get the order of rational approximation.

rational.type(): Get type of rational approximation.

Operator operations

Pr.mult() Pr.solve() Pl.mult() Pl.solve() Q.mult() Q.solve() Qsqrt.mult() Qsqrt.solve() Sigma.mult() Sigma.solve(): Operations with the Pr and Pl operators