povmap1.0.1 package

Extension to the 'emdi' Package

benchmark

Benchmark Function

combine_data

Combines Sample and Population Data

compare

Compare Function

compare_plot

Shows Plots for the Comparison of Estimates

compare_pred

Compare Predictions of Model Objects

data_transformation

Tranforms Dependent Variables

direct

Direct estimation of disaggregated indicators

ebp

Empirical Best Prediction for Disaggregated Indicators

ebp_compute_cv

Coefficient of Variation (CV) estimations for Unit EBP Model Headcount...

ebp_normalityfit

Output Model fit and normality assumptions

ebp_report_byrank

Produce EBP Head Count Population/Rate by Rank

ebp_reportcoef_table

Produce coefficient table for reporting

ebp_reportdescriptives

Create Descriptive Statistics for Small Area Estimation Report

ebp_test_means

Perform test for difference between survey and census means

emdi

A package for estimating and mapping disaggregated indicators

emdi_summaries

Summarizes an emdiObject

emdiObject

Fitted emdiObject

estimators

Presents Point, MSE and CV Estimates

fh

Standard and Extended Fay-Herriot Models for Disaggregated Indicators

fixef

Extract Fixed Effects from an emdi Object

getData

Extract emdi Object Data

getGroups

Extract Grouping Factors from an emdi Object

getGroupsFormula

Extract Grouping Formula from an emdi Object

getResponse

Extract Response Variable from an emdi Object

getVarCov

Extract Variance-covariance Matrix from an emdi Object

intervals

Confidence Intervals on Coefficients of an emdi Object

load_shapeaustria

Loading the Shape File for Austrian Districts

map_plot

Visualizes Regional Disaggregated Estimates on a Map

plot.emdi

Plots for an emdi Object

predict.emdi

Predictions from emdi Objects

qqnorm.emdi

Quantile-quantile Plots for an emdi Object

ranef

Extract Random Effects of emdi Objects

spatialcor.tests

Spatial Autocorrelation Tests

step

Step Function

write.excel

Exports an emdiObject to an Excel File or OpenDocument Spreadsheet

wtd.quantile

Quick function to estimate weighted quantiles

The R package 'povmap' supports small area estimation of means and poverty headcount rates. It adds several new features to the 'emdi' package (see "The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators" by Kreutzmann et al. (2019) <doi:10.18637/jss.v091.i07>). These include new options for incorporating survey weights, ex-post benchmarking of estimates, two additional transformations, several new convenient functions to assist with reporting results, and a wrapper function to facilitate access from 'Stata'.