Package index
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rSPDE
rSPDE-package
- Rational approximations of fractional SPDEs.
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rspde.matern()
- Matern rSPDE model object for INLA
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rspde.metric_graph()
- Matern rSPDE model object for metric graphs in INLA
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rspde.spacetime()
- Space-Time Random Fields via SPDE Approximation
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rspde.anistropic2d()
- Rational approximations of stationary anisotropic Gaussian Matern random fields
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rspde.matern1d()
- Matern rSPDE model object for INLA
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matern.operators()
- Rational approximations of stationary Gaussian Matern random fields
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matern2d.operators()
- Rational approximations of stationary anisotropic Gaussian Matern random fields
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spde.matern.operators()
- Rational approximations of non-stationary Gaussian SPDE Matern random fields
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fractional.operators()
- Rational approximations of fractional operators
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matern.rational()
- Rational approximation of the Matern fields on intervals and metric graphs
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spacetime.operators()
- Space-time random fields
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rspde_lme()
- rSPDE linear mixed effects models
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predict(<rspde_lme>)
- Prediction of a mixed effects regression model on a metric graph.
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summary(<rspde_lme>)
- Summary Method for
rspde_lme
Objects.
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glance(<rspde_lme>)
- Glance at an
rspde_lme
object
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augment(<rspde_lme>)
- Augment data with information from a
rspde_lme
object
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intrinsic.matern.operators()
- Covariance-based approximations of intrinsic fields
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variogram.intrinsic.spde()
- Variogram of intrinsic SPDE model
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rspde.intrinsic.matern()
- Intrinsic Matern rSPDE model object for INLA
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simulate(<intrinsicCBrSPDEobj>)
- Simulation of a fractional intrinsic SPDE using the covariance-based rational SPDE approximation
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rSPDE.matern.loglike()
- Object-based log-likelihood function for latent Gaussian fractional SPDE model using the rational approximations
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rSPDE.loglike()
- Object-based log-likelihood function for latent Gaussian fractional SPDE model
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spde.matern.loglike()
- Parameter-based log-likelihood for a latent Gaussian Matern SPDE model using a rational SPDE approximation
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rSPDE.construct.matern.loglike()
- Constructor of Matern loglikelihood functions.
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construct.spde.matern.loglike()
- Constructor of Matern loglikelihood functions for non-stationary models.
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rspde.matern.precision()
- Precision matrix of the covariance-based rational approximation of stationary Gaussian Matern random fields
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rspde.matern.precision.integer()
- Precision matrix of stationary Gaussian Matern random fields with integer covariance exponent
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predict(<rSPDEobj>)
- Prediction of a fractional SPDE using a rational SPDE approximation
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simulate(<rSPDEobj>)
- Simulation of a fractional SPDE using a rational SPDE approximation
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summary(<rSPDEobj>)
print(<summary.rSPDEobj>)
print(<rSPDEobj>)
- Summarise rSPDE objects
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update(<rSPDEobj>)
- Update parameters of rSPDEobj objects
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predict(<CBrSPDEobj>)
- Prediction of a fractional SPDE using the covariance-based rational SPDE approximation
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simulate(<CBrSPDEobj>)
- Simulation of a fractional SPDE using the covariance-based rational SPDE approximation
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summary(<CBrSPDEobj>)
print(<summary.CBrSPDEobj>)
print(<CBrSPDEobj>)
- Summarise CBrSPDE objects
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update(<CBrSPDEobj>)
- Update parameters of CBrSPDEobj objects
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precision()
- Get the precision matrix of CBrSPDEobj objects
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predict(<CBrSPDEobj2d>)
- Prediction of an anisotropic Whittle-Matern field
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simulate(<CBrSPDEobj2d>)
- Simulation of a fractional SPDE using the covariance-based rational SPDE approximation
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summary(<CBrSPDEobj2d>)
print(<summary.CBrSPDEobj2d>)
print(<CBrSPDEobj2d>)
- Summarise CBrSPDEobj2d objects
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update(<CBrSPDEobj2d>)
- Update parameters of CBrSPDEobj2d objects
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precision(<CBrSPDEobj2d>)
- Get the precision matrix of CBrSPDEobj2d objects
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simulate(<rSPDEobj1d>)
- Simulation of a Matern field using a rational SPDE approximation
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summary(<rSPDEobj1d>)
print(<summary.rSPDEobj1d>)
print(<rSPDEobj1d>)
- Summarise rSPDE objects without FEM
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update(<rSPDEobj1d>)
- Update parameters of rSPDEobj1d objects
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precision(<rSPDEobj1d>)
- Get the precision matrix of rSPDEobj1d objects
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precision(<spacetimeobj>)
- Get the precision matrix of spacetimeobj objects
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predict(<spacetimeobj>)
- Prediction of a space-time SPDE
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simulate(<spacetimeobj>)
- Simulation of space-time models
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update(<spacetimeobj>)
- Update parameters of spacetimeobj objects
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summary(<spacetimeobj>)
print(<summary.spacetimeobj>)
print(<spacetimeobj>)
- Summarise spacetime objects
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rspde.make.A()
- Observation/prediction matrices for rSPDE models.
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spde.make.A()
- Observation/prediction matrices for rSPDE models with integer smoothness.
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rspde.make.index()
- rSPDE model index vector generation
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graph_data_rspde()
- Data extraction from metric graphs for 'rSPDE' models
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rspde.mesh.project()
rspde.mesh.projector()
- Calculate a lattice projection to/from an
inla.mesh
for rSPDE objects
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rspde.result()
- rSPDE result extraction from INLA estimation results
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summary(<rspde_result>)
- Summary for posteriors of field parameters for an
inla_rspde
model from arspde_result
object
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precision(<inla_rspde>)
- Get the precision matrix of
inla_rspde
objects
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gg_df()
- Data frame for result objects from R-INLA fitted models to be used in ggplot2
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gg_df(<rspde_result>)
- Data frame for rspde_result objects to be used in ggplot2
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cross_validation()
- Perform cross-validation on a list of fitted models.
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group_predict()
- Perform prediction on a testing set based on a training set
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predict(<inla_rspde_matern1d>)
- Predict method for 'inlabru' stationary Matern 1d models
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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
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bru_get_mapper.inla_rspde_spacetime()
- rSPDE space time inlabru mapper
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bru_get_mapper.inla_rspde_anisotropic2d()
- rSPDE anisotropic inlabru mapper
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rSPDE.A1d()
- Observation matrix for finite element discretization on R
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rSPDE.fem1d()
- Finite element calculations for problems on R
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rSPDE.fem2d()
- Finite element calculations for problems in 2D
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rSPDE.Ast()
- Observation matrix for space-time models
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create_train_test_indices()
- Create train and test splits to be used in the
cross_validation
function
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get.initial.values.rSPDE()
- Initial values for log-likelihood optimization in rSPDE models with a latent stationary Gaussian Matern model
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require.nowarnings()
- Warnings free loading of add-on packages
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matern.covariance()
- The Matern covariance function
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matern.rational.cov()
- Rational approximation of the Matern covariance
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folded.matern.covariance.1d()
- The 1d folded Matern covariance function
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folded.matern.covariance.2d()
- The 2d folded Matern covariance function
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rspde.matern.precision.opt()
- Optimized precision matrix of the covariance-based rational approximation
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rspde.matern.precision.integer.opt()
- Optimized precision matrix of stationary Gaussian Matern random fields with integer covariance exponent
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`rational.order<-`()
- Changing the order of the rational approximation
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`rational.type<-`()
- Changing the type of the rational approximation
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rational.order()
- Get the order of rational approximation.
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rational.type()
- Get type of rational approximation.
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transform_parameters_anisotropic()
- Transform Anisotropic SPDE Model Parameters to Original Scale
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transform_parameters_spacetime()
- Transform Spacetime SPDE Model Parameters to Original Scale
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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