|
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 |
|
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 |
|
nations
|
Dataset 'nations' |
|
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 |
|
optimStrata()
|
Optimization of the stratification of a sampling frame given a sample survey |
|
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 |
|
errors
|
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 |
|
swissframe
|
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. |