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saebnocov
View on CRAN: Click
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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]
[Scholar Profile | Author Map]
All associated links for this package
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 25 Apr. 2025.
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imports, suggests or enhances
Complete documentation for saebnocov
Functions, R codes and Examples using
the saebnocov R package
Some associated functions: EBnaive . alphabetaEB . bootstrapEB . dataEB . estEBnaive . jackknifeEB . matrixClaire . matrixRao . momentClaire . momentRao . newtonRaphsonC . newtonRaphsonR . pcapdir . vectorClaire . vectorRao .
Some associated R codes: EBnaive.R . alfabetaEB.R . bootstrapEB.R . dataEB.R . direct.R . estEBnaive.R . jackknifeEB.R . matrixClaire.R . matrixRao.R . momentClaire.R . momentRao.R . newtonRaphsonC.R . newtonRaphsonR.R . pcapdir.R . vectorClaire.R . vectorRao.R . Full saebnocov package functions and examples
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