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]

saebnocov_0.1.0.tar.gz
saebnocov_0.1.0.zip(r-4.7-any)saebnocov_0.1.0.zip(r-4.6-any)saebnocov_0.1.0.zip(r-4.5-any)
saebnocov_0.1.0.tgz(r-4.6-any)saebnocov_0.1.0.tgz(r-4.5-any)
saebnocov_0.1.0.tar.gz(r-4.7-any)saebnocov_0.1.0.tar.gz(r-4.6-any)
saebnocov_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
saebnocov/json (API)

# Install 'saebnocov' in R:
install.packages('saebnocov', repos = c('https://fika-fianda.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • dataEB - Sample Data for Practice

On CRAN:

Conda:

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

2.30 score 6 scripts 229 downloads 14 exports 17 dependencies

Last updated from:5048522747. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK125
source / vignettesOK177
linux-releaseOK121
macos-releaseOK162
macos-oldrelOK131
windows-develOK75
windows-releaseOK67
windows-oldrelOK80
wasm-releaseOK101

Exports:alphabetaEBbootstrapEBEBnaiveestEBnaivejackknifeEBmatrixClairematrixRaomomentClairemomentRaonewtonRaphsonCnewtonRaphsonRpcapdirvectorClairevectorRao

Dependencies:clidescrdplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithrxtable

Best_Vignete_ever
Rendered fromBest_Vignete_ever.Rmdusingknitr::rmarkdown

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

Best_Vignetee_ever
Rendered fromBest_Vignetee_ever.Rmdusingknitr::rmarkdown

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