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.
Point_estimatethe estimated statistical indicators: Mean, Gini, Head-Count Ratio, Quantiles (10%, 25%, 50%, 75%, 90%), Poverty-Gap, Quintile-Share Ratio and if specified the selected custom indicators.
Standard_Errorif bootstrap.se = TRUE,
the standard errors for the statistical indicator are estimated
Mestimateskde object containing the corrected density estimate,
as in dclass
resultDensityestimated density for each iteration,
as in dclass
resultXtrue latent values X estimates,
as in dclass
xclassclassified values; factor with ordered factor values,
as in dclass
gridxgrid on which density is evaluated,
as in dclass
classesclasses; Inf as last value is allowed,
as in dclass
burninburn-in sample size,
as in dclass
samplessampling iteration size,
as in dclass
Point_estimates.runthe estimated statistical indicators: Mean, Gini, Head-Count Ratio, Quantiles (10%, 25%, 50%, 75%, 90%), Poverty-Gap, Quintile-Share Ratio and if specified the selected custom indicators for each iteration run of the KDE-algorithm
oecdthe weights used for the estimation of the equivalised household income
weightsany kind of survey or design weights that will be used for the weighted estimation of the statistical indicators
upperif the upper bound of the upper interval is Inf e.g.
(15000,Inf), then Inf is replaced by 15000*upper
Walter, P., Weimer, K. (2018). Estimating Poverty and Inequality Indicators using Interval Censored Income Data from the German Microcensus. FU-Berlin School of Business & Economics, Discussion Paper. Gro<U+00DF>, 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.