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SpatioTemporal (version 0.9.2)

Spatio-Temporal Model Estimation

Description

Utilities that estimate, predict and cross-validate the spatio-temporal model developed for MESA Air.

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Version

Install

install.packages('SpatioTemporal')

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Version

0.9.2

License

GPL-2

Maintainer

Johan Lindstrom

Last Published

March 8th, 2012

Functions in SpatioTemporal (0.9.2)

SVD.smooth.cv

Cross-validation for Smooth Basis Functions

estimateCV

Cross-Validated Estimation and Prediction

sumLogDiag

Sum the Logarithm of Diagonal Elements

calc.tF.times.mat

Compute Matrix Productes Involving the Smooth Trends

plotMonitoringLoc

Plot of Observation Locations and Dates

cond.expectation

Computes Conditional Expectation for Unobserved Locations

calc.smooth.trends

Smooth Basis Functions for a mesa.data Structure

block.mult

Multiplication of Block Diagonal Matrix and Vector

loglike

Compute the Log-likelihood for the Spatio-Temporal Model

combineMesaData

Merges two Data Objects.

plotCV

Illustrates Predictions and Cross-validated Predictions

default.LUR.list

Error Checking and Default Values for Covariate Selection

CVresiduals.qqnorm

QQ-norm and Scatterplots for Data and Residual Analysis

SVD.miss

Replace Missing Values in a Data Matrix Using Iterative svd.

loglike.var.names

Create Names for Log-likelihood Parameters

construct.LUR.basis

Extract and Create Covariate Matrices

mesa.data.raw

Example of raw data

SVD.smooth

Smooth Basis Functions for Data Matrix with Missing Values

createCV

Define Cross-Validation Groups

compute.ltaCV

Computes the long term average for each sites.

fit.mesa.model

Estimation of the Spatio-Temporal Model

dot.prod

Computes Inner Product and Squared 2-norm

loglike.grad

Compute Gradient and Hessian for the Log-likelihood

drop.observations

Drop Observations from mesa.data.model

gen.gradient

Compute Finite Difference Gradient and Hessians.

SpatioTemporal-package

Spatio-Temporal Modelling

calc.iS.X

Matrix Multiplication with Block Matrices

mesa.data

Example of a mesa.data Structure

make.sigma.nu

Crete (Cross)-Covariance Matrices for the Residual Field

remove.ST.mean

Mean-Centre the Spatio-Temporal Covariate

get.params

Extract Parameters from a Vector

mesa.data.res

Results of some time consuming code.

detrend.data

Removes the estimated time-trend from the observations in a mesa.data object.

make.sigma.B

Create Covariance Matrix for the beta-Fields

make.sigma.B.full

The Covariance Matrix for Temporal Trends and beta Fields.

summaryStatsCV

Computes Summary Statistics for Cross-validation

create.data.model

Creates the mesa.data.model structure; selection of model covariates

plotMesaData

Illustrates the Observations as Timeseries

create.data.matrix

Create a Data Matrix from a mesa.data Structure

printMesaDataNbrObs

Summary of Locations and Time Points

mesa.data.model

Example of a mesa.data.model Structure

makeCholBlock

Computations for Block Diagonal Matrices

tstat

Basic diagnostic statistics and summaries for SpatioTemporal model output.

setupSTdataset

Creates the data structure that is then used to build specific models via create.data.model.

predictNaive

Naive Temporal Predictions

simulateMesaData

Simulate Data from the Spatio-Temporal Model

loglike.dim

Dimensions of the Model Data Structure

run.MCMC

MCMC Inference of Parameters in the Spatio-Temporal Model.