Estimating and Mapping Disaggregated Indicators

Functions that support estimating, assessing and mapping regional disaggregated indicators. So far, estimation methods comprise direct estimation and the model-based approach Empirical Best Prediction (see "Small area estimation of poverty indicators" by Molina and Rao (2010) ), as well as their precision estimates. The assessment of the used model is supported by a summary and diagnostic plots. For a suitable presentation of estimates, map plots can be easily created. Furthermore, results can easily be exported to excel.


Reference manual

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1.1.1 by Soeren Pannier, 3 months ago

Browse source code at

Authors: Ann-Kristin Kreutzmann [aut], Soeren Pannier [aut, cre], Natalia Rojas-Perilla [aut], Timo Schmid [aut], Matthias Templ [aut], Nikos Tzavidis [aut]

Documentation:   PDF Manual  

GPL-2 license

Imports nlme, FNN, moments, ggplot2, MuMIn, gridExtra, openxlsx, ggmap, reshape2, graphics, stats, parallelMap, HLMdiag, parallel, simFrame, boot, rgeos, maptools, MASS

Suggests testthat, R.rsp, laeken

See at CRAN