emdi: Estimating and Mapping Disaggregated Indicators

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.

Author
Ann-Kristin Kreutzmann [aut], Soeren Pannier [cre], Natalia Rojas-Perilla [aut], Timo Schmid [aut], Nikos Tzavidis [aut], Matthias Templ [aut]
Date of publication
2016-11-08 16:50:36
Maintainer
Soeren Pannier <soeren.pannier@fu-berlin.de>
License
GPL-2
Version
1.0.0

View on CRAN

Man pages

data_transformation
Tranforms dependent variables
ebp
Empirical Best Prediction for disaggregated indicators
emdi
A package for estimating and mapping disaggregated indicators
emdiObject
Fitted emdiObject
estimators
Presents point, MSE and CV estimates
estimators.emdi
Presents point, MSE and/or CV estimates of an emdiObject
eusilcA_pop
Simulated eusilc data - population data
eusilcA_smp
Simulated eusilc data - sample data
head.estimators.emdi
Returns the first part of predicted indicators
map_plot
Visualises regional disaggregrated estimates on a map
plot.emdi
Plots for an emdi object
print.emdi
Prints an emdiObject
print.estimators.emdi
Prints estimators.emdi objects
print.summary.emdi
Prints a summary.emdi object
summary.emdi
Summarize an emdiObjecz
tail.estimators.emdi
Returns the last part of predicted indicators
write.excel
Exports an emdiObject to an excel file

Files in this package

emdi
emdi/inst
emdi/inst/shapes
emdi/inst/shapes/shape_austria_dis.RData
emdi/tests
emdi/tests/testthat.R
emdi/tests/testthat
emdi/tests/testthat/ebp_MSE_bc_out.csv
emdi/tests/testthat/ebp_point_log.csv
emdi/tests/testthat/test_ebp.R
emdi/tests/testthat/ebp_shift_bc_out.csv
emdi/tests/testthat/data_bc.csv
emdi/tests/testthat/Xoutsamp_AuxVar.RData
emdi/tests/testthat/incomedata_woTeruel.RData
emdi/tests/testthat/test_mse_estimation.R
emdi/tests/testthat/data_bc_std.csv
emdi/tests/testthat/ebp_MSE_no.csv
emdi/tests/testthat/ebp_optpar_bc.csv
emdi/tests/testthat/ebp_MSE_bc.csv
emdi/tests/testthat/incomedata.RData
emdi/tests/testthat/ebp_shift_bc.csv
emdi/tests/testthat/ebp_test.xlsx
emdi/tests/testthat/ebp_point_bc_out.csv
emdi/tests/testthat/ebp_test.csv
emdi/tests/testthat/ebp_optpar_bc_out.csv
emdi/tests/testthat/data_log.csv
emdi/tests/testthat/ebp_point_no.csv
emdi/tests/testthat/test_data_transformation.R
emdi/tests/testthat/ebp_MSE_log.csv
emdi/tests/testthat/ebp_shift_log.csv
emdi/tests/testthat/ebp_point_bc.csv
emdi/tests/testthat/test_optimal_par.R
emdi/tests/testthat/excel_output_all.xlsx
emdi/tests/testthat/test_point_estimation.R
emdi/NAMESPACE
emdi/data
emdi/data/eusilcA_smp.rda
emdi/data/eusilcA_pop.rda
emdi/R
emdi/R/indicator_functions.R
emdi/R/summary.emdi.R
emdi/R/transformation_functions.R
emdi/R/plot.emdi.R
emdi/R/check_ebp_arguments.R
emdi/R/eusilcA_pop.R
emdi/R/mse_estimation.R
emdi/R/optimal_parameter.R
emdi/R/mse_emdi.R
emdi/R/print.emdi.R
emdi/R/point_estimation.R
emdi/R/emdi.R
emdi/R/framework.R
emdi/R/emdiObject.R
emdi/R/point_emdi.R
emdi/R/write.excel.emdi.R
emdi/R/ebp.R
emdi/R/eusilcA_smp.R
emdi/R/map_plot.R
emdi/R/estimators.emdi.R
emdi/MD5
emdi/DESCRIPTION
emdi/man
emdi/man/print.emdi.Rd
emdi/man/map_plot.Rd
emdi/man/data_transformation.Rd
emdi/man/write.excel.Rd
emdi/man/head.estimators.emdi.Rd
emdi/man/estimators.Rd
emdi/man/ebp.Rd
emdi/man/tail.estimators.emdi.Rd
emdi/man/print.summary.emdi.Rd
emdi/man/estimators.emdi.Rd
emdi/man/print.estimators.emdi.Rd
emdi/man/summary.emdi.Rd
emdi/man/eusilcA_pop.Rd
emdi/man/eusilcA_smp.Rd
emdi/man/emdi.Rd
emdi/man/emdiObject.Rd
emdi/man/plot.emdi.Rd