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?
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