Package: BayesSampling 1.1.0

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>.

Authors:Pedro Soares Figueiredo [aut, cre], Kelly C. M. Gonçalves [aut, ths]

BayesSampling_1.1.0.tar.gz
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BayesSampling_1.1.0.tgz(r-4.6-any)BayesSampling_1.1.0.tgz(r-4.5-any)
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BayesSampling_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BayesSampling/json (API)

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

Bug tracker:https://github.com/pedrosfig/bayessampling/issues

Datasets:
  • BigCity - Full Person-level Population Database

On CRAN:

Conda:

bayesianestimatorsampling

4.73 score 1 stars 18 scripts 300 downloads 5 exports 4 dependencies

Last updated from:13095496b1. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE122
source / vignettesOK174
linux-release-x86_64NOTE119
macos-release-arm64NOTE158
macos-oldrel-arm64NOTE163
windows-develNOTE109
windows-releaseNOTE86
windows-oldrelNOTE85
wasm-releaseOK99

Exports:BLE_CategoricalBLE_RatioBLE_RegBLE_SRSBLE_SSRS

Dependencies:latticeMASSMatrixmatrixcalc

BLE_Categorical
Application of the BLE to categorical data | (From Section 4 of the "Gonçalves, Moura and Migon: Bayes linear estimation for finite population with emphasis on categorical data") | Vague Prior Distribution | R and Vs Matrices | Examples
Rendered fromBLE_Categorical.Rmdusingknitr::rmarkdown

Last update: 2021-05-01
Started: 2021-03-21

BLE_SRS
Application of the BLE to the Simple Random Sample design | (From Section 2.3.1 of the "Gonçalves, Moura and Migon: Bayes linear estimation for finite population with emphasis on categorical data") | Vague Prior Distribution | Examples
Rendered fromBLE_SRS.Rmdusingknitr::rmarkdown

Last update: 2021-03-21
Started: 2020-02-18

BLE_Ratio
Application of the BLE to the Ratio estimator | (From Section 3 of the "Gonçalves, Moura and Migon: Bayes linear estimation for finite population with emphasis on categorical data") | Application | Vague Prior Distribution | Examples
Rendered fromBLE_Ratio.Rmdusingknitr::rmarkdown

Last update: 2020-11-23
Started: 2020-02-18

BLE_SSRS
Application of the BLE to the Stratified Simple Random Sample design | (From Section 2.3.2 of the "Gonçalves, Moura and Migon: Bayes linear estimation for finite population with emphasis on categorical data") | Examples
Rendered fromBLE_SSRS.Rmdusingknitr::rmarkdown

Last update: 2020-11-23
Started: 2020-02-18

BayesSampling
Bayes linear estimation for finite population | (From "Gonçalves, Moura and Migon: Bayes linear estimation for finite population with emphasis on categorical data") | 1. Introduction | 2. Bayes linear estimation for finite population | 2.1 Bayes linear approach | 3. Functions
Rendered fromBayesSampling.Rmdusingknitr::rmarkdown

Last update: 2020-04-10
Started: 2020-02-18

BLE_Reg
Bayes linear approach to finite population | (From Section 2.2 of the "Gonçalves, Moura and Migon: Bayes linear estimation for finite population with emphasis on categorical data") | Application | Examples
Rendered fromBLE_Reg.Rmdusingknitr::rmarkdown

Last update: 2020-04-10
Started: 2020-02-18