Package: emdi
Title: Estimating and Mapping Disaggregated Indicators
Version: 1.0.0
Authors@R: c(person("Ann-Kristin", "Kreutzmann", role="aut", email="ann-kristin.kreutzmann@fu-berlin.de"),
    person("Soeren", "Pannier", role="cre", email="soeren.pannier@fu-berlin.de"),
    person("Natalia", "Rojas-Perilla", role="aut", email = "natalia.rojas@fu-berlin.de"),
    person("Timo", "Schmid", role="aut", email = "timo.schmid@fu-berlin.de"),
    person("Nikos", "Tzavidis", role="aut", email = "N.TZAVIDIS@soton.ac.uk"),
    person("Matthias", "Templ", role="aut", email = "templ@statistik.tuwien.ac.at"))
Description: Functions that support estimating, assessing and mapping regional disaggregated indicators. So far, estimation methods comprise the model-based approach Empirical Best Prediction (see "Small area estimation of poverty indicators" by Molina and Rao (2010)<doi:10.1002/cjs.10051>), 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.
Depends: R (>= 3.3.0), maptools
License: GPL-2
LazyData: true
RoxygenNote: 5.0.1
Imports: nlme, FNN, moments, ggplot2, MuMIn, gridExtra, openxlsx,
        ggmap, reshape2, graphics, stats, parallelMap, HLMdiag,
        parallel, simFrame
Suggests: testthat
NeedsCompilation: no
Packaged: 2016-11-08 13:05:28 UTC; SP
Author: Ann-Kristin Kreutzmann [aut],
  Soeren Pannier [cre],
  Natalia Rojas-Perilla [aut],
  Timo Schmid [aut],
  Nikos Tzavidis [aut],
  Matthias Templ [aut]
Maintainer: Soeren Pannier <soeren.pannier@fu-berlin.de>
Repository: CRAN
Date/Publication: 2016-11-08 16:50:36
