Post-estimation problem with beta-regression user command dfmlogit after fmlogit

[ericmelse]

I am exercising the examples of the user packages betafit, zoib, dirifit and fmlogit, of Maarten Buis (more here), which are discussed in this presentation.
My interest is in fitting a fractional multinomial logit model but I fail to run the post-estimation command dfmlogit.
If you can repeat this code (I run Stata 15.1, ver. 10-15-2018):

* Get the packages:
ssc install dirifit , replace
ssc install fmlogit , replace

* Get the data file:
use http://fmwww.bc.edu/repec/bocode/c/citybudget.dta, clear

* Run the model fitting a Dirichlet distribution by maximum likelihood as well as the post-estimation command:
dirifit governing safety education recreation social urbanplanning, ///
    mu(minorityleft noleft houseval popdens)

ddirifit, at(minorityleft 0 noleft 0 )
// Results are omitted here, but all should run fine.

* Run the model fitting a Dirichlet distribution by maximum likelihood as well as the post-estimation command:
fmlogit governing safety education recreation social urbanplanning, ///
    eta(minorityleft noleft houseval popdens)

dfmlogit, at(minorityleft 0 noleft 0 )
// Results are omitted here, but only the model runs on my system but not the post-estimation command, which prompts the user with an error statement (text is from the ado file):
// dfmlogit only exists for older versions of Stata
// use margins instead

It might make sense that the post-estimation command is incompatible with the latest version of Stata.
However, the ado-file dates: *! version 1.3.0 MLB 14Feb2017, which suggests to me that it should run in some version mode.
This I tried to do, like with:

version 8: dfmlogit, at(minorityleft 0 noleft 0 )

but it will not work (on my system).

So, three questions:

1. Can anyone reproduce the same error prompt?
2. Would anyone know if and how it is possible to run dfmlogit?
3. And, if that is not possible, can someone show me how margins can give the same post-estimation results as dfmlogit would provide, as explained on pages 32 and 33 of the presentation.

Any help is much appreciated.