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laeken (version 0.4.4)

Estimation of indicators on social exclusion and poverty

Description

Estimation of indicators on social exclusion and poverty, as well as Pareto tail modeling for empirical income distributions.

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Version

Install

install.packages('laeken')

Monthly Downloads

13,016

Version

0.4.4

License

GPL (>= 2)

Maintainer

Andreas Alfons

Last Published

April 2nd, 2013

Functions in laeken (0.4.4)

laeken-package

Estimation of indicators on social exclusion and poverty
ses

Synthetic SES survey data
thetaHill

Hill estimator
thetaISE

Integrated squared error (ISE) estimator
meanExcessPlot

Mean excess plot
bootVar

Bootstrap variance and confidence intervals of indicators on social exclusion and poverty
incMedian

Weighted median income
thetaPDC

Partial density component (PDC) estimator
variance

Variance and confidence intervals of indicators on social exclusion and poverty
thetaWML

Weighted maximum likelihood estimator
shrinkOut

Shrink outliers in the Pareto model
fitPareto

Fit income distribution models with the Pareto distribution
minAMSE

Weighted asymptotic mean squared error (AMSE) estimator
eqInc

Equivalized disposable income
incQuintile

Weighted income quintile
thetaLS

Least squares (LS) estimator
arpr

At-risk-of-poverty rate
rmpg

Relative median at-risk-of-poverty gap
paretoScale

Estimate the scale parameter of a Pareto distribution
weightedMedian

Weighted median
weightedMean

Weighted mean
plot.paretoTail

Diagnostic plot for the Pareto tail model
qsr

Quintile share ratio
calibVars

Construct a matrix of binary variables for calibration
gini

Gini coefficient
paretoQPlot

Pareto quantile plot
utils

Utility functions for indicators on social exclusion and poverty
incMean

Weighted mean income
arpt

At-risk-of-poverty threshold
thetaTM

Trimmed mean estimator
eqSS

Equivalized household size
paretoTail

Pareto tail modeling for income distributions
calibWeights

Calibrate sample weights
thetaQQ

QQ-estimator
gpg

Gender pay (wage) gap.
thetaMoment

Moment estimator
reweightOut

Reweight outliers in the Pareto model
eusilc

Synthetic EU-SILC survey data
replaceTail

Replace observations under a Pareto model
weightedQuantile

Weighted quantiles