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saebnocov  

Small Area Estimation using Empirical Bayes without Auxiliary Variable
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("saebnocov", "0.1.0")



Attach the package and use:
library("saebnocov")
Maintained by
Siti Rafika Fiandasari
[Scholar Profile | Author Map]
First Published: 2022-09-05
Latest Update: 2022-09-05
Description:
Estimates the parameter of small area in binary data without auxiliary variable using Empirical Bayes technique, mainly from Rao and Molina (2015,ISBN:9781118735787) with book entitled "Small Area Estimation Second Edition". This package provides another option of direct estimation using weight. This package also features alpha and beta parameter estimation on calculating process of small area. Those methods are Newton-Raphson and Moment which based on Wilcox (1979) and Kleinman (1973) .
How to cite:
Siti Rafika Fiandasari (2022). saebnocov: Small Area Estimation using Empirical Bayes without Auxiliary Variable. R package version 0.1.0, https://cran.r-project.org/web/packages/saebnocov. Accessed 29 Mar. 2025.
Previous versions and publish date:
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Complete documentation for saebnocov
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