Functions that support estimating, assessing and mapping regional
disaggregated indicators. So far, estimation methods comprise direct estimation,
the model-based unit-level approach Empirical Best Prediction (see "Small area
estimation of poverty indicators" by Molina and Rao (2010)
compare_plotnow benefits from a legend in all plots.
compare_plothas been added to allow for an easy comparison between direct and model based estimates.
map_plotin order to explain the mapping table
ebpbenefits from a new parameter called
seedthat allows reproducibility even when the function is run in parallel mode.
directis made available, which provides direct estimation for small areas.
ebpnow allows for a user-defined threshold.
ebpis now able to perform a semi-parametric wild bootstrap for MSE estimation.
ebphas new default value for parallelization that automatically adopts for the operating system.
eusilcA_pophave been updated.
map_plotadditional customization is now applicable.
emdi modelexcept plot are extended for
as.data.framehave been added as methods for class