BayesSampling: Bayes Linear Estimators for Finite Population

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
Author: Pedro Soares Figueiredo ORCID iD [aut, cre], Kelly C. M. Gonçalves ORCID iD [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

Downloads:

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-release (x86_64): BayesSampling_1.1.0.tgz, r-oldrel: BayesSampling_1.1.0.tgz
Old sources: BayesSampling archive

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