Package: saebnocov 0.1.0

saebnocov: Small Area Estimation using Empirical Bayes without Auxiliary Variable

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) <doi:10.1177/001316447903900302> and Kleinman (1973) <doi:10.1080/01621459.1973.10481332>.

Authors:Siti Rafika Fiandasari [aut, cre], Margaretha Ari Anggorowati [aut], Bahrul Ilmi Nasution [aut]

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saebnocov.pdf |saebnocov.html
saebnocov/json (API)

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

Peer review:

Datasets:
  • dataEB - Sample Data for Practice

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.30 score 3 scripts 181 downloads 14 exports 18 dependencies

Last updated 2 years agofrom:5048522747. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 11 2024
R-4.5-winOKOct 11 2024
R-4.5-linuxOKOct 11 2024
R-4.4-winOKOct 11 2024
R-4.4-macOKOct 11 2024
R-4.3-winOKOct 11 2024
R-4.3-macOKOct 11 2024

Exports:alphabetaEBbootstrapEBEBnaiveestEBnaivejackknifeEBmatrixClairematrixRaomomentClairemomentRaonewtonRaphsonCnewtonRaphsonRpcapdirvectorClairevectorRao

Dependencies:clidescrdplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithrxtable

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Last update: 2022-09-05
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Last update: 2022-09-05
Started: 2022-09-05