Different Methods for Stratified Sampling
Sequential balanced sampling
Balanced Stratification
Statistical matching using optimal transport and balanced sampling
C bound
C bound
Calibration using raking ratio
Conditional Poisson sampling design
Disjunctive
Disjunctive for matrix
Squared Euclidean distances of the unit k.
Fast Balanced Sampling
Fast flight phase of the cube method
Find best sub-matrix B in stratifiedcube
Generalized calibration using raking ratio
Harmonization by calibration
Inclusion Probabilities
Landing by suppression of variables
Joint inclusion probabilities of maximum entropy.
Number of categories
One-step One Decision sampling method
Statistical Matching using Optimal transport
pik from q
pikt from pik
q from w
s from q
Stratified Sampling
Deville's systematic
Second order inclusion probabilities of Deville's systematic
Approximated variance for balanced sample
Approximated variance for balanced sampling
Estimator of the approximated variance for balanced sampling
Variance Estimation for Doubly Balanced Sample.
Variance Estimation for balanced sample
Integrating a stratified structure in the population in a sampling design can considerably reduce the variance of the Horvitz-Thompson estimator. We propose in this package different methods to handle the selection of a balanced sample in stratified population. For more details see Raphaël Jauslin, Esther Eustache and Yves Tillé (2021) <doi:10.1007/s42081-021-00134-y>. The package propose also a method based on optimal transport and balanced sampling, see Raphaël Jauslin and Yves Tillé <doi:10.1016/j.jspi.2022.12.003>.
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