Spatio-Temporal Model Estimation


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Documentation for package ‘SpatioTemporal’ version 0.9.0

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SpatioTemporal-package Spatio-Temporal Modelling
block.mult Multiplication of Block Diagonal Matrix and Vector
block_mult Internal C-functions
calc.F.times.X Compute Matrix Productes Involving the Smooth Trends
calc.iS.X Matrix Multiplication with Block Matrices
calc.mu.B Matrix Multiplication with Block Matrices
calc.smooth.trends Smooth Basis Functions for a mesa.data Structure
calc.tF.mat.F Compute Matrix Productes Involving the Smooth Trends
calc.tF.times.mat Compute Matrix Productes Involving the Smooth Trends
calc.X.iS.X Matrix Multiplication with Block Matrices
calc_F_part_X Internal C-functions
calc_tF_mat_F Internal C-functions
calc_tF_times_mat Internal C-functions
combineMesaData Merges two Data Objects.
compute.ltaCV Computes the long term average for each sites.
cond.expectation Computes Conditional Expectation for Unobserved Locations
construct.LUR.basis Extract and Create Covariate Matrices
construct.ST.basis Extract and Create Covariate Matrices
create.data.matrix Create a Data Matrix from a mesa.data Structure
create.data.model Creates the mesa.data.model structure; selection of model covarites
createCV Define Cross-Validation Groups
CVresiduals.qqnorm QQ-norm and Scatterplots for Data and Residual Analysis
CVresiduals.scatter QQ-norm and Scatterplots for Data and Residual Analysis
default.LUR.list Error Checking and Default Values for Covariate Selection
default.ST.list Error Checking and Default Values for Covariate Selection
dot.prod Computes Inner Product and Squared 2-norm
dot_prod Internal C-functions
drop.observations Drop Observations from mesa.data.model
estimateCV Cross-Validated Estimation and Prediction
fit.mesa.model Estimation of the Spatio-Temporal Model
gen.gradient Compute Finite Difference Gradient and Hessians.
gen.hessian Compute Finite Difference Gradient and Hessians.
get.params Extract Parameters from a Vector
invCholBlock Computations for Block Diagonal Matrices
inv_chol_block Internal C-functions
loglike Compute the Log-likelihood for the Spatio-Temporal Model
loglike.dim Dimensions of the Model Data Structure
loglike.grad Compute Gradient and Hessian for the Log-likelihood
loglike.hessian Compute Gradient and Hessian for the Log-likelihood
loglike.naive Compute the Log-likelihood for the Spatio-Temporal Model
loglike.naive.grad Compute Gradient and Hessian for the Log-likelihood
loglike.naive.hessian Compute Gradient and Hessian for the Log-likelihood
loglike.var.names Create Names for Log-likelihood Parameters
make.sigma.B Create Covariance Matrix for the beta-Fields
make.sigma.B.full The Covariance Matrix for Temporal Trends and beta Fields.
make.sigma.nu Crete (Cross)-Covariance Matrices for the Residual Field
make.sigma.nu.cross.cov Crete (Cross)-Covariance Matrices for the Residual Field
makeCholBlock Computations for Block Diagonal Matrices
make_chol_block Internal C-functions
make_sigma_b Internal C-functions
make_sigma_b_full Internal C-functions
make_sigma_nu Internal C-functions
make_sigma_nu_cross_cov Internal C-functions
mesa.data Example of a mesa.data Structure
mesa.data.model Example of a mesa.data.model Structure
mesa.data.raw Example of raw data
mesa.data.res Results of some time consuming code.
norm2 Computes Inner Product and Squared 2-norm
norm2_c Internal C-functions
plotCV Illustrates Predictions and Cross-validated Predictions
plotMesaData Illustrates the Observations as Timeseries
plotMonitoringLoc Plot of Observation Locations and Dates
plotPrediction Illustrates Predictions and Cross-validated Predictions
predictCV Cross-Validated Estimation and Prediction
predictNaive Naive Temporal Predictions
printMesaDataNbrObs Summary of Locations and Time Points
remove.ST.mean Mean-Centre the Spatio-Temporal Covariate
run.MCMC MCMC Inference of Parameters in the Spatio-Temporal Model.
simulateMesaData Simulate Data from the Spatio-Temporal Model
solveTriBlock Computations for Block Diagonal Matrices
solve_tri_block Internal C-functions
SpatioTemporal Spatio-Temporal Modelling
sumLogDiag Sum the Logarithm of Diagonal Elements
summaryStatsCV Computes Summary Statistics for Cross-validation
sum_log_diag Internal C-functions
SVD.miss Replace Missing Values in a Data Matrix Using Iterative svd.
SVD.smooth Smooth Basis Functions for Data Matrix with Missing Values
SVD.smooth.cv Cross-validation for Smooth Basis Functions