emdi (1.1.7)

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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. For a detailed description of the package and the methods used see "The {R} Package {emdi} for Estimating and Mapping Regionally Disaggregated Indicators" by Kreutzmann et al. (2019) .

Maintainer: Soeren Pannier
Author(s): Ann-Kristin Kreutzmann [aut], Soeren Pannier [aut, cre], Natalia Rojas-Perilla [aut], Timo Schmid [aut], Matthias Templ [aut], Nikos Tzavidis [aut]

License: GPL-2

Uses: boot, ggplot2, gridExtra, HLMdiag, maptools, MASS, moments, MuMIn, nlme, openxlsx, parallelMap, readODS, reshape2, rgeos, R.rsp, simFrame, testthat, laeken

Released 19 days ago.

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