Estimation of the Generalised Beta Distribution of the Second
Kind from Grouped Data
Vanesa Jorda <jordav@unican.es>, Jose Maria Sarabia
<jose.sarabia@unican.es>, Markus Jäntti <markus.jantti@sofi.su.se>.
Estimation of the generalized beta distribution of the second
kind (GB2) and related models using grouped data in form of income shares.
The GB2 family is a general class of distributions that provides an accurate
fit to income data. 'GB2group' includes functions to estimate the GB2, the
Singh-Maddala, the Dagum, the Beta 2, the Lognormal and the Fisk distributions.
'GB2group' deploys two different econometric strategies to estimate these
parametric distributions, non-linear least squares (NLS) and the generalised
method of moments (GMM). Asymptotic standard errors are reported for the
GMM estimates. Standard errors of the NLS estimates are obtained by Monte
Carlo simulation. See Jorda et al. (2018) <arXiv:1808.09831> for a detailed
description of the estimation procedure.

Estimation of the generalized beta distribution of the second
kind (GB2) and related models using grouped data in form of income shares.
The GB2 family is a general class of distributions that provides an accurate
fit to income data. 'GB2group' includes functions to estimate the GB2, the
Singh-Maddala, the Dagum, the Beta 2, the Lognormal and the Fisk distributions.
'GB2group' deploys two different econometric strategies to estimate these
parametric distributions, the equally weighted minimum distance (EWMD) estimator and the
optimally weighted minimum distance (OMD) estimator. Asymptotic standard errors are reported for the
OMD estimates. Standard errors of the EWMD estimates are obtained by Monte
Carlo simulation. See Jorda et al. (2018) <arXiv:1808.09831> for a detailed
description of the estimation procedure.

Generalized Berk-Jones Statistic for Set-Based Inference
Offers the Generalized Berk-Jones (GBJ) test for set-based inference in genetic
association studies. The GBJ is designed as an alternative to tests such as Berk-Jones (BJ),
Higher Criticism (HC), Generalized Higher Criticism (GHC), Minimum p-value (minP), and Sequence
Kernel Association Test (SKAT). All of these other methods (except for SKAT) are also implemented
in this package, and we  additionally provide an omnibus test (OMNI) which integrates information from each of the tests.
The GBJ has been shown to outperform other tests in genetic association studies when signals
are correlated and moderately sparse. For more details, please ask for a preprint of our
manuscript or see the vignette for a quickstart guide.