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msaeOB  

Optimum Benchmarking for Multivariate Small Area Estimation
View on CRAN: Click here


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

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

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



Attach the package and use:
library("msaeOB")
Maintained by
Muhammad Yasqi Imanda
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-14
Latest Update: 2023-04-03
Description:
Implements multivariate optimum benchmarking small area estimation. This package provides optimum benchmarking estimation for univariate and multivariate small area estimation and its MSE. In fact, MSE estimators for optimum benchmark are not readily available, so resampling method that called parametric bootstrap is applied. The optimum benchmark model and parametric bootstrap in this package are based on the model proposed in small area estimation. J.N.K Rao and Isabel Molina (2015, ISBN: 978-1-118-73578-7).
How to cite:
Muhammad Yasqi Imanda (2022). msaeOB: Optimum Benchmarking for Multivariate Small Area Estimation. R package version 0.1.0, https://cran.r-project.org/web/packages/msaeOB
Previous versions and publish date:
0.1.0 (2022-03-14 20:50)
Other packages that cited msaeOB R package
View msaeOB citation profile
Other R packages that msaeOB depends, imports, suggests or enhances
Functions, R codes and Examples using the msaeOB R package
Some associated functions: datamsaeOB . datamsaeOBns . est_msaeOB . est_msaeOBns . est_saeOB . est_saeOBns . mse_msaeOB . mse_msaeOBns . mse_saeOB . mse_saeOBns . 
Some associated R codes: datamsaeOB.R . datamsaeOBns.R . est_msaeOB.R . est_msaeOBns.R . est_saeOB.R . est_saeOBns.R . mse_msaeOB.R . mse_msaeOBns.R . mse_saeOB.R . mse_saeOBns.R .  Full msaeOB package functions and examples
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