KmeansSolution          Initial solution obtained by applying kmeans
                        clustering of atomic strata
KmeansSolution2         Initial solution obtained by applying kmeans
                        clustering of frame units
KmeansSolutionSpatial   Initial solution obtained by applying kmeans
                        clustering of frame units
adjustSize              Adjustment of the sample size in case it is
                        externally given
aggrStrata2             Builds the "strata" dataframe containing
                        information on target variables Y's
                        distributions in the different strata, starting
                        from a frame
aggrStrataSpatial       Builds the "strata" dataframe containing
                        information on target variables Y's
                        distributions in the different strata, starting
                        from a frame where units are spatially
                        correlated.
assignStrataLabel       Function to assign the optimized strata labels
bethel                  Multivariate optimal allocation
buildFrameDF            Builds the "sampling frame" dataframe from a
                        dataset containing information on all the units
                        in the population of reference
buildFrameSpatial       Builds the "sampling frame" dataframe from a
                        dataset containing information all the units in
                        the population of reference including spatial
buildStrataDF           Builds the "strata" dataframe containing
                        information on target variables Y's
                        distributions in the different strata, starting
                        from sample data or from a frame
buildStrataDFSpatial    Builds the "strata" dataframe containing
                        information on target variables Y's
                        distributions in the different strata, starting
                        from sample data or from a frame
checkInput              Checks the inputs to the package: dataframes
                        "errors", "strata" and "sampling frame"
computeGamma            Function that allows to calculate a
                        heteroscedasticity index, together with
                        associate prediction variance, to be used by
                        the optimization step to correctly evaluate the
                        standard deviation in the strata due to
                        prediction errors.
errors                  Precision constraints (maximum CVs) as input
                        for Bethel allocation
evalSolution            Evaluation of the solution produced by the
                        function 'optimizeStrata' by selecting a number
                        of samples from the frame with the optimal
                        stratification, and calculating average CV's on
                        the target variables Y's.
expected_CV             Expected coefficients of variation of target
                        variables Y
nations                 Dataset 'nations'
optimStrata             Optimization of the stratification of a
                        sampling frame given a sample survey
optimizeStrata          Best stratification of a sampling frame for
                        multipurpose surveys
optimizeStrata2         Best stratification of a sampling frame for
                        multipurpose surveys (only with continuous
                        stratification variables)
optimizeStrataSpatial   Best stratification of a sampling frame for
                        multipurpose surveys considering also spatial
                        correlation
plotSamprate            Plotting sampling rates in the different strata
                        for each domain in the solution.
plotStrata2d            Plot bivariate distibutions in strata
prepareSuggestion       Prepare suggestions for optimization with
                        method = "continuous" or "spatial"
procBethel              Procedure to apply Bethel algorithm and select
                        a sample from given strata
selectSample            Selection of a stratified sample from the frame
                        with srswor method
selectSampleSpatial     Selection of geo-referenced points from the
                        frame
selectSampleSystematic
                        Selection of a stratified sample from the frame
                        with systematic method
strata                  Dataframe containing information on strata in
                        the frame
summaryStrata           Information on strata structure
swisserrors             Precision constraints (maximum CVs) as input
                        for Bethel allocation
swissframe              Dataframe containing information on all units
                        in the population of reference that can be
                        considered as the final sampling unit (this
                        example is related to Swiss municipalities)
swissmunicipalities     The Swiss municipalities population
swissstrata             Dataframe containing information on strata in
                        the swiss municipalities frame
tuneParameters          Execution and compared evaluation of
                        optimization runs
updateFrame             Updates the initial frame on the basis of the
                        optimized stratification
updateStrata            Assigns new labels to atomic strata on the
                        basis of the optimized aggregated strata
var.bin                 Allows to transform a continuous variable into
                        a categorical ordinal one by applying a
                        modified version of the k-means clustering
                        function in the 'stats' package.
