Description Value References See Also
An object of class "kdeAlgo" that represents the estimated
statistical indicators and the estimated standard errors.
Objects of this class have methods for the generic functions
print
and plot
.
An object of class "kdeAlgo" is a list containing at least the following components.

the estimated statistical indicators: Mean, Gini, HeadCount Ratio, Quantiles (10%, 25%, 50%, 75%, 90%), PovertyGap, QuintileShare Ratio and if specified the selected custom indicators. 

if 

kde object containing the corrected density estimate,
as in 

estimated density for each iteration,
as in 

true latent values X estimates,
as in 

classified values; factor with ordered factor values,
as in 

grid on which density is evaluated,
as in 

classes; Inf as last value is allowed,
as in 

burnin sample size,
as in 

sampling iteration size,
as in 

the estimated statistical indicators: Mean, Gini, HeadCount Ratio, Quantiles (10%, 25%, 50%, 75%, 90%), PovertyGap, QuintileShare Ratio and if specified the selected custom indicators for each iteration run of the KDEalgorithm 

the weights used for the estimation of the equivalised household income 

any kind of survey or design weights that will be used for the weighted estimation of the statistical indicators 

if the upper bound of the upper interval is 
Walter, P., Weimer, K. (2018). Estimating Poverty and Inequality Indicators
using Interval Censored Income Data from the German Microcensus.
FUBerlin School of Business & Economics, Discussion
Paper.
Gro<c3><9f>, M., U. Rendtel, T. Schmid, S. Schmon, and N. Tzavidis (2017).
Estimating the density of ethnic minorities and aged people in Berlin: Multivariate
Kernel Density Estimation applied to sensitive georeferenced administrative data
protected via measurement error. Journal of the Royal Statistical Society: Series A
(Statistics in Society), 180.
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