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) <>.

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>
License: GPL-3
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: BayesSampling results


Reference manual: BayesSampling.pdf
Vignettes: BLE_Categorical
Package source: BayesSampling_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


Please use the canonical form to link to this page.