Package: Frames2 0.2.1

Frames2: Estimation in Dual Frame Surveys

Point and interval estimation in dual frame surveys. In contrast to classic sampling theory, where only one sampling frame is considered, dual frame methodology assumes that there are two frames available for sampling and that, overall, they cover the entire target population. Then, two probability samples (one from each frame) are drawn and information collected is suitably combined to get estimators of the parameter of interest.

Authors:Antonio Arcos <[email protected]>, Maria del Mar Rueda <[email protected]>, Maria Giovanna Ranalli <[email protected]> and David Molina <[email protected]>

Frames2_0.2.1.tar.gz
Frames2_0.2.1.zip(r-4.5)Frames2_0.2.1.zip(r-4.4)Frames2_0.2.1.zip(r-4.3)
Frames2_0.2.1.tgz(r-4.4-any)Frames2_0.2.1.tgz(r-4.3-any)
Frames2_0.2.1.tar.gz(r-4.5-noble)Frames2_0.2.1.tar.gz(r-4.4-noble)
Frames2_0.2.1.tgz(r-4.4-emscripten)Frames2_0.2.1.tgz(r-4.3-emscripten)
Frames2.pdf |Frames2.html
Frames2/json (API)

# Install 'Frames2' in R:
install.packages('Frames2', repos = c('https://dmolinam.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Dat - Joint sample database
  • DatA - Database of household expenses for frame A
  • DatB - Database of household expenses for frame B
  • DatMA - Database of students' program choice for frame A
  • DatMB - Database of students' program choice for frame B
  • DatPopM - Database of auxiliary information for the whole population of students
  • PiklA - Matrix of inclusion probabilities for units selected in sample from frame A
  • PiklB - Matrix of inclusion probabilities for units selected in sample from frame B

On CRAN:

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

35 exports 0.00 score 4 dependencies 44 scripts 228 downloads

Last updated 9 years agofrom:eff6878036. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 16 2024
R-4.5-winOKSep 16 2024
R-4.5-linuxOKSep 16 2024
R-4.4-winOKSep 16 2024
R-4.4-macOKSep 16 2024
R-4.3-winOKSep 16 2024
R-4.3-macOKSep 16 2024

Exports:BKACalDFCalSFCompareCovHTDomainsFBHartleyHTJackBKAJackCalDFJackCalSFJackFBJackHartleyJackMLCDFJackMLCDWJackMLCSWJackMLDFJackMLDWJackMLSWJackPELJackPMLJackSFRRMLCDFMLCDWMLCSWMLDFMLDWMLSWPELPMLSFRRVarHTWeightsCalDFWeightsCalSF

Dependencies:lpSolveMASSnnetsampling

Estimation in a dual frame context

Rendered fromestimation.Rnwusingutils::Sweaveon Sep 16 2024.

Last update: 2015-12-12
Started: 2013-07-17

Splitting and formatting data in a dual frame context

Rendered fromformatting.data.Rnwusingutils::Sweaveon Sep 16 2024.

Last update: 2015-12-12
Started: 2013-07-17

Readme and manuals

Help Manual

Help pageTopics
Bankier-Kalton-Anderson estimatorBKA
DF calibration estimatorCalDF
SF calibration estimatorCalSF
Summary of estimatorsCompare
Covariance estimator between two Horvitz - Thompson estimatorsCovHT
Joint sample databaseDat
Database of household expenses for frame ADatA
Database of household expenses for frame BDatB
Database of students' program choice for frame ADatMA
Database of students' program choice for frame BDatMB
Database of auxiliary information for the whole population of studentsDatPopM
DomainsDomains
Fuller-Burmeister estimatorFB
Hartley estimatorHartley
Horvitz - Thompson estimatorHT
Confidence intervals for Bankier-Kalton-Anderson estimator based on jackknife methodJackBKA
Confidence intervals for dual frame calibration estimator based on jackknife methodJackCalDF
Confidence intervals for SF calibration estimator based on jackknife methodJackCalSF
Confidence intervals for Fuller-Burmeister estimator based on jackknife methodJackFB
Confidence intervals for Hartley estimator based on jackknife methodJackHartley
Confidence intervals for MLCDF estimator based on jackknife methodJackMLCDF
Confidence intervals for MLCDW estimator based on jackknife methodJackMLCDW
Confidence intervals for MLCSW estimator based on jackknife methodJackMLCSW
Confidence intervals for MLDF estimator based on jackknife methodJackMLDF
Confidence intervals for MLDW estimator based on jackknife methodJackMLDW
Confidence intervals for MLSW estimator based on jackknife methodJackMLSW
Confidence intervals for the pseudo empirical likelihood estimator based on jackknife methodJackPEL
Confidence intervals for the pseudo maximum likelihood estimator based on jackknife methodJackPML
Confidence intervals for raking ratio estimator based on jackknife methodJackSFRR
Multinomial logistic calibration estimator under dual frame approach with auxiliary information from each frameMLCDF
Multinomial logistic calibration estimator under dual frame approach with auxiliary information from the whole populationMLCDW
Multinomial logistic calibration estimator under single frame approach with auxiliary information from the whole populationMLCSW
Multinomial logistic estimator under dual frame approach with auxiliary information from each frameMLDF
Multinomial logistic estimator under dual frame approach with auxiliary information from the whole populationMLDW
Multinomial logistic estimator under single frame approach with auxiliary information from the whole populationMLSW
Pseudo empirical likelihood estimatorPEL
Matrix of inclusion probabilities for units selected in sample from frame APiklA
Matrix of inclusion probabilities for units selected in sample from frame BPiklB
Pseudo Maximum Likelihood estimatorPML
Raking ratio estimatorSFRR
Variance estimator of Horvitz - Thompson estimatorVarHT
g-weights for the dual frame calibration estimatorWeightsCalDF
g-weights for the SF calibration estimatorWeightsCalSF