Allows the user to apply the Bayes Linear approach to finite population with the Simple Random Sampling - BLE_SRS() - and the Stratified Simple Random Sampling design - BLE_SSRS() - (both without replacement), to the Ratio estimator (using auxiliary information) - BLE_Ratio() - and to categorical data - BLE_Categorical(). The Bayes linear estimation approach is applied to a general linear regression model for finite population prediction in BLE_Reg() and it is also possible to achieve the design based estimators using vague prior distributions. Based on Gonçalves, K.C.M, Moura, F.A.S and Migon, H.S.(2014) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886>.
Version: | 1.1.0 |
Depends: | R (≥ 3.5) |
Imports: | MASS, Matrix, stats, matrixcalc |
Suggests: | knitr, rmarkdown, TeachingSampling |
Published: | 2021-05-01 |
DOI: | 10.32614/CRAN.package.BayesSampling |
Author: | Pedro Soares Figueiredo [aut, cre], Kelly C. M. Gonçalves [aut, ths] |
Maintainer: | Pedro Soares Figueiredo <pedrosfig at hotmail.com> |
License: | GPL-3 |
URL: | https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886, https://github.com/pedrosfig/BayesSampling |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README |
CRAN checks: | BayesSampling results |
Reference manual: | BayesSampling.pdf |
Vignettes: |
BLE_Categorical BLE_Ratio BLE_Reg BLE_SRS BLE_SSRS BayesSampling |
Package source: | BayesSampling_1.1.0.tar.gz |
Windows binaries: | r-devel: BayesSampling_1.1.0.zip, r-release: BayesSampling_1.1.0.zip, r-oldrel: BayesSampling_1.1.0.zip |
macOS binaries: | r-release (arm64): BayesSampling_1.1.0.tgz, r-oldrel (arm64): BayesSampling_1.1.0.tgz, r-release (x86_64): BayesSampling_1.1.0.tgz, r-oldrel (x86_64): BayesSampling_1.1.0.tgz |
Old sources: | BayesSampling archive |
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