GetARegionBK            Get a Regional Kriging
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
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.
rSquared                Coefficient of Determination
rmse                    RMSE function
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
