# Constrained Spatiotemporal Mixed Models for Exposure Estimation

## Documentation for package ‘sptemExp’ version 0.1.3

- DESCRIPTION file.

## Help Pages

abatchModel | A Batch Modeing Training Inner Functions
allPre500 | The dataset of the prediction result for some days for 2014 Shandong, interpolated by constrained optimization.
bKriging | Regional Mean Estimation by Block Kriging
bnd | BND spatial topology data for use in spatial effect modeling.
colorCusGrinf | Customed Color Generation by the Number of the Levels
colorGrinf | Generation of Customed Gradient Colors
conOpt | Function of Constrained Optimization
countylayer | County layer map for illustration of block Kriging.
exeCluster | Efficient Clustering Using Union-Find to Obtain the Clusters for Each Sample
extractVNC4 | Extract Values for Point from NC4 Image
extractVTIF | Extract GeoTiff Data
fillNASVD | Function to Use SVD to Impute the Missing Values for Training Dataset
fillNASVDSer | SVD to Interpolate the Missing Values in the Time Series Data
genRaster | Generation of Raster Covering the Side Map
GetARegionBK | Get a Regional Kriging
getClusterCt | Retrieve the Central Coordinates for Each Cluser after Clustering Done.
getPolyMMean | Generation of Regional Monthly Mean Based on the Input Polygons
getRidbytpoly | getRidbytpoly for Assignment of Thiessen polygon id to point object
getTBasisFun | Generation of Temporal Basis Function
getTidBKMean | Batch Block Kriging for Estimate of Regional Means
gtifRst | The 2014 time series of PM2.5 concentrations of Shandong province, with many missing values.
inter2conOpt | Batch Interpolation of the Missing Values for Time Series Using Constrained Optimization.
noweiAvg | Averages over the Ensemble Predictions of Mixed Models (No weighted)
parATimePredict | Batch Prediction for Time Series Using the Ensemble Models
parSpModel | Generation of Spatiotemporal Models by Bootstrap Aggregating
parTemporalBImp | Function to Fill Missing Values by Constraint Optimization
perMdPrediction | Batch Prediction Using the Trained Models
points2Raster | Generation of Grid Surface Using the predicted/Interpolated Values
pol_season_trends | pol_season_trends .
prnside | Side to limit the Thiessen's polygons.
rmse | RMSE function
rSquared | Coefficient of Determination
samplepnt | Sample data for generation of Thiessen polygons.
shd140401pcovs | The dataset of 04/01/2014 prediction dataset for the raster spoint_pre covering the Shandong with 2km x 2km grid .
shdSeries2014 | The 2014 time series of PM2.5 concentrations of Shandong province, with missing approach.
spointspre | SpatialPointDataFrame as container of raster to geo-link with the specific date prediction of PM2.5.
tpolygonsByBorder | tpolygonsByBorder for Generation of Thiessen polygons
trainsample | The dataset of 2014 training sample for the Shandong with missing values imputed using SVD.
voronoipolygons2 | Generation of Thiesseon Polygons By Points
weiA2Ens | Ensemble Weighted Prediction of Mixed Models
weightedstat | Weighted Average for Multiple Models