binequality looks like just the package I need, specifically for obtaining Gini income coefficients for binned data. I have upgraded to the latest version of R, the latest version of RStudio, and updated all packages. Still I have a persistent problem using fitFunc(). To keep things simple, I am testing things using the example code in the binequality manual, page 6 (or, "?fitFunc"). However, it exhibits the same problems as does my code and another example found elsewhere on the Internet, namely NA results for all fields of interest, as follows: Time difference of 0.776551 secs for LNO fit across 2 distributions $datOut State obsMean distribution estMean var cv cv_sqr gini theil MLD 1 California NA LNO NA NA NA NA NA NA NA 2 Texas NA LNO NA NA NA NA NA NA NA SDL aic bic didConverge logLikelihood nparams median sd 1 NA NA NA FALSE NA NA NA NA 2 NA NA NA FALSE NA NA NA NA $timeStamp [1] 1497327774 $parameters mu sigma nu tau California NA NA NA NA Texas NA NA NA NA $quantiles NULL To summarise, I have tried fitFunc() in my own code and it produced similar results to that above. I found another example (for a different purpose) and tried it, and it also gave these results. Finally, trying the example in the fitFunc example code proves that the results are (i) consistent and (ii) not what any of the three authors would be expecting. Any thoughts? [[alternative HTML version deleted]]