Optimal Stratification of Sampling Frames for Multipurpose Sampling Surveys


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Documentation for package ‘SamplingStrata’ version 1.1

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bethel Multivariate optimal allocation
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
checkInput Checks the inputs to the package: dataframes "errors", "strata" and "sampling frame"
errors Precision constraints (maximum CVs) as input for Bethel allocation
evalSolution Allows to evaluate 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 together with differences between estimates and the values of the parameters in the population.
optimizeStrata Best stratification of a sampling frame for multipurpose surveys
plotSamprate Plotting sampling rates in the different strata for each domain in the solution.
selectSample Selection of a stratified sample from the frame with srswor method
strata Dataframe containing information on strata in the frame
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.