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maSAE  

Mandallaz' Model-Assisted Small Area Estimators
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("maSAE", "2.0.3")



Attach the package and use:
library("maSAE")
Maintained by
Andreas Dominik Cullmann
[Scholar Profile | Author Map]
First Published: 2014-04-28
Latest Update: 2021-04-12
Description:
An S4 implementation of the unbiased extension of the model- assisted synthetic-regression estimator proposed by Mandallaz (2013) , Mandallaz et al. (2013) and Mandallaz (2014) . It yields smaller variances than the standard bias correction, the generalised regression estimator.
How to cite:
Andreas Dominik Cullmann (2014). maSAE: Mandallaz' Model-Assisted Small Area Estimators. R package version 2.0.3, https://cran.r-project.org/web/packages/maSAE. Accessed 02 May. 2025.
Previous versions and publish date:
0.1-2 (2014-04-28 07:10), 0.1-3 (2015-07-03 01:26), 0.1-4 (2016-02-26 14:12), 0.1-5 (2016-05-31 11:10), 1.0.0 (2020-01-10 01:20), 2.0.0 (2020-03-13 19:50), 2.0.1 (2020-03-23 15:50), 2.0.2 (2020-11-02 21:40)
Other packages that cited maSAE R package
View maSAE citation profile
Other R packages that maSAE depends, imports, suggests or enhances
Complete documentation for maSAE
Functions, R codes and Examples using the maSAE R package
Some associated functions: bind_data . maSAE-internal . maSAE-package . predict-methods . s0 . s1 . s2 . saObj . sadObj-class . saeObj-class . savObj-class . throw . 
Some associated R codes: allClasses.R . allConstructors.R . allGenerics.R . bind_data.R . data.R . maSAE-package.R . predict-functions.R . predict-functions_old.R . predict-methods.R . throw.R .  Full maSAE package functions and examples
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