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BayesSampling  

Bayes Linear Estimators for Finite Population
View on CRAN: Click here


Download and install BayesSampling package within the R console
Install from CRAN:
install.packages("BayesSampling")

Install from Github:
library("remotes")
install_github("cran/BayesSampling")

Install by package version:
library("remotes")
install_version("BayesSampling", "1.1.0")



Attach the package and use:
library("BayesSampling")
Maintained by
Pedro Soares Figueiredo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-04-24
Latest Update: 2021-05-01
Description:
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 Gon
How to cite:
Pedro Soares Figueiredo (2020). BayesSampling: Bayes Linear Estimators for Finite Population. R package version 1.1.0, https://cran.r-project.org/web/packages/BayesSampling. Accessed 06 Aug. 2026.
Previous versions and publish date:
1.0.0 (2020-04-24 18:30), (2026-07-09 07:58)
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Complete documentation for BayesSampling
Functions, R codes and Examples using the BayesSampling R package
Some associated functions: BLE_Categorical . BLE_Ratio . BLE_Reg . BLE_SRS . BLE_SSRS . BigCity . C . E_beta . E_theta_Reg . T_Reg . VT_Reg . V_beta . V_theta_Reg . create1 . 
Some associated R codes: BLE_Reg.R . Data.R . categorical.R . create1.R . imports.R . sample_designs.R .  Full BayesSampling package functions and examples
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