The aim of this package is to offer new methodology for unitlevel small area models under transformations and limited population auxiliary information. In addition to this new methodology, the widely used nested error regression model without transformations (see "An ErrorComponents Model for Prediction of County Crop Areas Using Survey and Satellite Data" by Battese, Harter and Fuller (1988) <doi:10.1080/01621459.1988.10478561>) and its wellknown uncertainty estimate (see "The estimation of the mean squared error of smallarea estimators" by Prasad and Rao (1990) <doi:10.1080/01621459.1995.10476570>) are provided. In this package, the log transformation and the datadriven logshift transformation are provided. If a transformation is selected, an appropriate method is chosen depending on the respective input of the population data: Individual population data (see "Empirical best prediction under a nested error model with log transformation" by Molina and Martín (2018) <doi:10.1214/17aos1608>) but also aggregated population data (see "Estimating regional income indicators under transformations and access to limited population auxiliary information" by Würz, Schmid and Tzavidis <unpublished>) can be entered. Especially under limited data access, new methodologies are provided in saeTrafo. Several options are available to assess the used model and to judge, present and export its results. For a detailed description of the package and the methods used see the corresponding vignette.
Package details 


Author  Nora Würz [aut] 
Maintainer  Nora Würz <nora.wuerz@unibamberg.de> 
License  GPL2 
Version  1.0.4 
URL  https://github.com/NoraWuerz/saeTrafo 
Package repository  View on CRAN 
Installation 
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