Package: sampling 2.10

sampling: Survey Sampling

Functions to draw random samples using different sampling schemes are available. Functions are also provided to obtain (generalized) calibration weights, different estimators, as well some variance estimators.

Authors:Yves Tillé <[email protected]>, Alina Matei <[email protected]>

sampling_2.10.tar.gz
sampling_2.10.zip(r-4.5)sampling_2.10.zip(r-4.4)sampling_2.10.zip(r-4.3)
sampling_2.10.tgz(r-4.4-x86_64)sampling_2.10.tgz(r-4.4-arm64)sampling_2.10.tgz(r-4.3-x86_64)sampling_2.10.tgz(r-4.3-arm64)
sampling_2.10.tar.gz(r-4.5-noble)sampling_2.10.tar.gz(r-4.4-noble)
sampling_2.10.tgz(r-4.4-emscripten)sampling_2.10.tgz(r-4.3-emscripten)
sampling.pdf |sampling.html✨
sampling/json (API)

# Install 'sampling' in R:
install.packages('sampling', repos = c('https://alinamateikondylis.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

62 exports 2 stars 4.05 score 2 dependencies 29 dependents 4 mentions 564 scripts 4.5k downloads

Last updated 11 months agofrom:d4fa205ca6. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 20 2024
R-4.5-win-x86_64OKAug 20 2024
R-4.5-linux-x86_64OKAug 20 2024
R-4.4-win-x86_64OKAug 20 2024
R-4.4-mac-x86_64OKAug 20 2024
R-4.4-mac-aarch64OKAug 20 2024
R-4.3-win-x86_64OKAug 20 2024
R-4.3-mac-x86_64OKAug 20 2024
R-4.3-mac-aarch64OKAug 20 2024

Exports:.as_intbalancedclusterbalancedstratificationbalancedtwostagecalibcalibevcheckcalibrationcleanstrataclusterdisjunctivefastflightcubegencalibgetdataHajekestimatorHajekstrataHTestimatorHTstratainclusionprobabilitiesinclusionprobastratalandingcubemstagepostestpoststrataratioestratioest_strataregestregest_stratarhgrhg_stratarmodelsamplecubesrsworsrswor1srswrstrataUPbrewerUPmaxentropyUPmaxentropypi2UPMEpik2frompikwUPMEpikfromqUPMEpiktildefrompikUPMEqfromwUPMEsfromqUPmidzunoUPmidzunopi2UPminimalsupportUPmultinomialUPopipsUPpivotalUPpoissonUPrandompivotalUPrandomsystematicUPsampfordUPsampfordpi2UPsystematicUPsystematicpi2UPtilleUPtillepi2varestvarHTvartaylor_ratiowritesample

Dependencies:lpSolveMASS

calibration and adjustment for nonresponse

Rendered fromcalibration.Snwusingutils::Sweaveon Aug 20 2024.

Last update: 2023-10-29
Started: 2015-06-30

Horvitz-Thompson estimator and Hajek estimator

Rendered fromHT_Hajek_estimators.Snwusingutils::Sweaveon Aug 20 2024.

Last update: 2023-10-29
Started: 2015-06-30

UP - unequal probability sampling designs

Rendered fromUPexamples.Snwusingutils::Sweaveon Aug 20 2024.

Last update: 2023-10-29
Started: 2015-06-30

Readme and manuals

Help Manual

Help pageTopics
Balanced clusterbalancedcluster
Balanced stratificationbalancedstratification
Balanced two-stage samplingbalancedtwostage
The Belgian municipalities populationbelgianmunicipalities
g-weights of the calibration estimatorcalib
Calibration estimator and its variance estimationcalibev
Check calibrationcheckcalibration
Clean stratacleanstrata
Cluster samplingcluster
Disjunctive combinationdisjunctive
Fast flight phase for the cube methodfastflightcube
g-weights of the generalized calibration estimatorgencalib
Get datagetdata
The Hajek estimatorHajekestimator
The Hajek estimator for a stratified designHajekstrata
The Horvitz-Thompson estimatorHTestimator
The Horvitz-Thompson estimator for a stratified designHTstrata
Inclusion probabilitiesinclusionprobabilities
Inclusion probabilities for a stratified designinclusionprobastrata
Landing phase for the cube methodlandingcube
Multistage samplingmstage
The MU284 populationMU284
Poststratified estimatorpostest
Postratificationpoststrata
Ratio estimatorratioest
Ratio estimator for a stratified designratioest_strata
The 1999 census datarec99
Regression estimatorregest
Regression estimator for a stratified designregest_strata
Response homogeneity groupsrhg
Response homogeneity groups for a stratified samplingrhg_strata
Response probability using logistic regressionrmodel
Sample cube methodsamplecube
Simple random sampling without replacementsrswor
Selection-rejection methodsrswor1
Simple random sampling with replacementsrswr
Stratified samplingstrata
The Swiss municipalities populationswissmunicipalities
Brewer samplingUPbrewer
Maximum entropy samplingUPmaxentropy UPmaxentropypi2 UPMEpik2frompikw UPMEpikfromq UPMEpiktildefrompik UPMEqfromw UPMEsfromq
Midzuno samplingUPmidzuno
Joint inclusion probabilities for Midzuno samplingUPmidzunopi2
Minimal support samplingUPminimalsupport
Multinomial samplingUPmultinomial
Order pips samplingUPopips
Pivotal samplingUPpivotal
Poisson samplingUPpoisson
Random pivotal samplingUPrandompivotal
Random systematic samplingUPrandomsystematic
Sampford samplingUPsampford
Joint inclusion probabilities for Sampford samplingUPsampfordpi2
Systematic samplingUPsystematic
Joint inclusion probabilities for systematic samplingUPsystematicpi2
Tille samplingUPtille
Joint inclusion probabilties for Tille samplingUPtillepi2
Variance estimation using the Deville's methodvarest
Variance estimators of the Horvitz-Thompson estimatorvarHT
Taylor-series linearization variance estimation of a ratiovartaylor_ratio
All possible samples of fixed sizewritesample