[kedar badu]

stata 16.1 to be precise

[kedar badu]

I'd like to uninstall ado/hlp files installed from ssc install dataex ... please help.

[Andrew Musau]

dataex is part of your official Stata installation for version 16. To uninstall the one installed from SSC

ssc uninstall dataex

[kedar badu]

thank you very much

[Jacob Ladenburg]

After running mixlogitwtp with no problems i suddenly get this error message "scores returned by evaluator not conformable with the groups". it is on data normally converge with no problem.. have any experienced the same

[Clyde Schechter]

#20 is wildly off-topic for this thread. Please repost in a New Topic.

[Fredrick orwa]

[16] package parallel from http://fmwww.bc.edu/repec/bocode/p
'PARALLEL': module for Parallel Computing

[17] package parallel from https://raw.github.com/gvegayon/parallel/master
'PARALLEL': module for Parallel Computing

[18] package parallel from https://raw.github.com/gvegayon/parallel/stable
'PARALLEL': module for Parallel Computing

[19] package parallel from https://raw.github.com/gvegayon/parallel/master
'PARALLEL': module for Parallel Computing

[20] package parallel from http://fmwww.bc.edu/repec/bocode/p
'PARALLEL': module for Parallel Computing

[21] package parallel from http://fmwww.bc.edu/repec/bocode/p
'PARALLEL': module for Parallel Computing

. ssc uninstall parallel
criterion matches more than one package
r(111);

Dear Clyde,
I know this question was asked long ago but I find myself in the same hole.I want to uninstall parallel and I get above error. I can manually delete the parralel associated ado (parallel_append.do,parallel.do, e.t.c) from "/Users/fodiwuor/Library/Application Support/Stata/ado/plus/p".But when I list packages I still see the above 4 parallel package installed from different urls.
kindly help.

[Clyde Schechter]

If you have tried the approaches shown in #1 through #12 of this thread and they have not led to success, I don't know how to help you. Hopefully somebody else who knows more about this will respond.

[Rich Goldstein]

I recently had the same issue and here is what tech support basically told me - edit the stata.trk file (it's an ASCII file) in your PLUS folder; be very careful when doing so; I had the OS (Mac) make a duplicate before I tried it so that I could easily get it back if I screwed up but it worked fine in my case; you want to delete the extra listings within this file - look carefully at the entries so that you know which lines start and end an entry and thus which to delete

[Fredrick orwa]

d
d fre displays, for each specified variable, a univariate
d frequency table containing counts, percent, and cumulative
d percent. Variables may be string or numeric. Labels, in full
d length, and values are printed. By default, fre only tabulates
d the smallest and largest 10 values (along with all missing
d values), but this can be changed. Furthermore, values with zero
d observed frequency may be included in the tables. The default
d for fre is to display the frequency tables in the results
d window. Alternatively, the tables may be written to a file on
d disk, either tab-delimited or LaTeX-formatted.
d
d KW: data management
d KW: frequencies
d KW: frequency table
d KW: tabulation
d
d Requires: Stata version 9.2
d
d Distribution-Date: 20210531
d
d Author: Ben Jann, University of Bern
d Support: email jann@@soz.unibe.ch
d
f f/fre.ado
f f/fre.hlp
e
S http://fmwww.bc.edu/repec/bocode/p
N parallel.pkg
D 20 Jun 2024
U 17
d 'PARALLEL': module for Parallel Computing
d
d Parallel lets you run Stata faster, sometimes faster than MP
d itself. By organizing your job in several Stata instances,
d parallel allows you to work with out-of-the-box parallel
d computing. Using the the 'parallel' prefix, you can get faster
d simulations, bootstrapping, reshaping big data, etc. without
d having to know a thing about parallel computing. With no need of
d having Stata/MP installed on your computer, parallel has showed
d to dramatically speedup computations up to two, four, or more
d times depending on how many processors your computer has.
d
d KW: parallel computing
d KW: timming
d KW: high performance computing
d KW: HPC
d KW: big data
d KW: simulations
d KW: bootstrapping
d KW: monte carlo
d KW: multiple imputations
d
d Requires: Stata version 11
d
d Distribution-Date: 20150829
d
d Author: George Vega Yon , Superintendencia de Pensiones, Chile
d Support: email gvega@@spensiones.cl
d
d Author: Brian Quistorff, University of Maryland
d Support: email bquistorff@@gmail.com
d
f p/parallel.ado
f p/parallel_append.ado
f p/parallel_bs.ado
f p/parallel_sim.ado
f p/parallel.sthlp
f p/parallel_source.sthlp
f l/lparallel.mlib
e
S https://raw.github.com/gvegayon/parallel/master
N parallel.pkg
D 23 Jun 2024
U 18
d 'PARALLEL': module for Parallel Computing
d
d Inspired in the R library "snow" and to be used in multicore
d CPUs, parallel implements parallel computing methods through
d OS's shell scripting (using Stata in batch mode) to accelerate
d computations. By starting a determined number of new Stata
d instances (child processes), this module allows the user to
d implement parallel computing methods without the need of having
d StataMP installed. Common tasks include vectorized operations,
d reshaping big data, running simulations (monte carlo experiments)
d or bootstrapping estimations. Depending on the number of cores of
d the CPU, parallel can reach linear speed ups significantly
d reducing computing wall-clock time.
d
d This current version includes the following commands:
d - parallel do for running dofiles.
d - parallel : for vectorized commands.
d - parallel bs for bootstrapping.
d - parallel sim for simulations.
d - parallel append for handlying multiple dta files.
d
d Finally parallel is, to the d author's knowledge, the first user
d contributed Stata module to implement parallel computing.
d
d KW: parallel computing
d KW: timming
d KW: high performance computing
d KW: HPC
d KW: big data
d KW: simulations
d KW: bootstrapping
d KW: monte carlo
d KW: multiple imputations
d
d Requires: Stata version 14
d
d Distribution-Date: 20231018
d
d Authors: George Vega Yon , California Institute of Technology, USA
d Brian Quistorff, Bureau of Economic Analysis, USA
d Support: email vegayon@@usc.edu
d
f c/cmd_list.ado
f _/_cmd_list_runner.ado
f c/cmd_list.sthlp
f p/parallel.ado
f p/parallel_append.ado
f p/parallel_bs.ado
f p/parallel_sim.ado
f p/parallel.sthlp
f p/parallel_source.sthlp
f l/lparallel.mlib
f p/procenv.ado
f p/procexec.ado
f p/procexecw.ado
f b/bshell.ado
f b/bshell.sthlp
f p/prockill.ado
f p/procwait.ado
f _/_seeded_cmd_wrapper.ado
f _/_seeded_runner.ado
f s/seeding.ado
f s/seeding.sthlp
e
S https://raw.github.com/gvegayon/parallel/stable
N parallel.pkg
D 24 Jun 2024
U 19
d 'PARALLEL': module for Parallel Computing
d
d Inspired in the R library "snow" and to be used in multicore
d CPUs, parallel implements parallel computing methods through
d OS's shell scripting (using Stata in batch mode) to accelerate
d computations. By starting a determined number of new Stata
d instances (child processes), this module allows the user to
d implement parallel computing methods without the need of having
d StataMP installed. Common tasks include vectorized operations,
d reshaping big data, running simulations (monte carlo experiments)
d or bootstrapping estimations. Depending on the number of cores of
d the CPU, parallel can reach linear speed ups significantly
d reducing computing wall-clock time.
d
d This current version includes the following commands:
d - parallel do for running dofiles.
d - parallel : for vectorized commands.
d - parallel bs for bootstrapping.
d - parallel sim for simulations.
d - parallel append for handlying multiple dta files.
d
d Finally parallel is, to the d author's knowledge, the first user
d contributed Stata module to implement parallel computing.
d
d KW: parallel computing
d KW: timming
d KW: high performance computing
d KW: HPC
d KW: big data
d KW: simulations
d KW: bootstrapping
d KW: monte carlo
d KW: multiple imputations
d
d Requires: Stata version 11
d
d Distribution-Date: 20190319
d
d Authors: George Vega Yon , California Institute of Technology, USA
d Brian Quistorff, Microsoft AI and Research, USA
d Support: email vegayon@@usc.edu
d
f p/parallel.ado
f p/parallel_append.ado
f p/parallel_bs.ado
f p/parallel_sim.ado
f p/parallel.sthlp
f p/parallel_source.sthlp
f l/lparallel.mlib
f p/procenv.ado
f p/procexec.ado
f p/prockill.ado
f p/procwait.ado
e
S https://raw.github.com/gvegayon/parallel/master
N parallel.pkg
D 24 Jun 2024
U 20
d 'PARALLEL': module for Parallel Computing
d
d Inspired in the R library "snow" and to be used in multicore
d CPUs, parallel implements parallel computing methods through
d OS's shell scripting (using Stata in batch mode) to accelerate
d computations. By starting a determined number of new Stata
d instances (child processes), this module allows the user to
d implement parallel computing methods without the need of having
d StataMP installed. Common tasks include vectorized operations,
d reshaping big data, running simulations (monte carlo experiments)
d or bootstrapping estimations. Depending on the number of cores of
d the CPU, parallel can reach linear speed ups significantly
d reducing computing wall-clock time.
d
d This current version includes the following commands:
d - parallel do for running dofiles.
d - parallel : for vectorized commands.
d - parallel bs for bootstrapping.
d - parallel sim for simulations.
d - parallel append for handlying multiple dta files.
d
d Finally parallel is, to the d author's knowledge, the first user
d contributed Stata module to implement parallel computing.
d
d KW: parallel computing
d KW: timming
d KW: high performance computing
d KW: HPC
d KW: big data
d KW: simulations
d KW: bootstrapping
d KW: monte carlo
d KW: multiple imputations
d
d Requires: Stata version 14
d
d Distribution-Date: 20231018
d
d Authors: George Vega Yon , California Institute of Technology, USA
d Brian Quistorff, Bureau of Economic Analysis, USA
d Support: email vegayon@@usc.edu
d
f c/cmd_list.ado
f _/_cmd_list_runner.ado
f c/cmd_list.sthlp
f p/parallel.ado
f p/parallel_append.ado
f p/parallel_bs.ado
f p/parallel_sim.ado
f p/parallel.sthlp
f p/parallel_source.sthlp
f l/lparallel.mlib
f p/procenv.ado
f p/procexec.ado
f p/procexecw.ado
f b/bshell.ado
f b/bshell.sthlp
f p/prockill.ado
f p/procwait.ado
f _/_seeded_cmd_wrapper.ado
f _/_seeded_runner.ado
f s/seeding.ado
f s/seeding.sthlp
e
S http://fmwww.bc.edu/repec/bocode/p
N parallel.pkg
D 24 Jun 2024
U 21
d 'PARALLEL': module for Parallel Computing
d
d Parallel lets you run Stata faster, sometimes faster than MP
d itself. By organizing your job in several Stata instances,
d parallel allows you to work with out-of-the-box parallel
d computing. Using the the 'parallel' prefix, you can get faster
d simulations, bootstrapping, reshaping big data, etc. without
d having to know a thing about parallel computing. With no need of
d having Stata/MP installed on your computer, parallel has showed
d to dramatically speedup computations up to two, four, or more
d times depending on how many processors your computer has.
d
d KW: parallel computing
d KW: timming
d KW: high performance computing
d KW: HPC
d KW: big data
d KW: simulations
d KW: bootstrapping
d KW: monte carlo
d KW: multiple imputations
d
d Requires: Stata version 11
d
d Distribution-Date: 20150829
d
d Author: George Vega Yon , Superintendencia de Pensiones, Chile
d Support: email gvega@@spensiones.cl
d
d Author: Brian Quistorff, University of Maryland
d Support: email bquistorff@@gmail.com
d
f p/parallel.ado
f p/parallel_append.ado
f p/parallel_bs.ado
f p/parallel_sim.ado
f p/parallel.sthlp
f p/parallel_source.sthlp
f l/lparallel.mlib
e
S http://fmwww.bc.edu/repec/bocode/p
N parallel.pkg
D 24 Jun 2024
U 22
d 'PARALLEL': module for Parallel Computing
d
d Parallel lets you run Stata faster, sometimes faster than MP
d itself. By organizing your job in several Stata instances,
d parallel allows you to work with out-of-the-box parallel
d computing. Using the the 'parallel' prefix, you can get faster
d simulations, bootstrapping, reshaping big data, etc. without
d having to know a thing about parallel computing. With no need of
d having Stata/MP installed on your computer, parallel has showed
d to dramatically speedup computations up to two, four, or more
d times depending on how many processors your computer has.
d
d KW: parallel computing
d KW: timming
d KW: high performance computing
d KW: HPC
d KW: big data
d KW: simulations
d KW: bootstrapping
d KW: monte carlo
d KW: multiple imputations
d
d Requires: Stata version 11
d
d Distribution-Date: 20150829
d
d Author: George Vega Yon , Superintendencia de Pensiones, Chile
d Support: email gvega@@spensiones.cl
d
d Author: Brian Quistorff, University of Maryland
d Support: email bquistorff@@gmail.com
d
f p/parallel.ado
f p/parallel_append.ado
f p/parallel_bs.ado
f p/parallel_sim.ado
f p/parallel.sthlp
f p/parallel_source.sthlp
f l/lparallel.mlib
e
Hi Rich should I delete everything from d Requires: Stata version 9.2 .the place have marked in bold downwards? in

[Fredrick orwa]

Thanks so much Rich.The trick has worked for me

[Hemanshu Kumar]

It's also possible to delete packages using the number in square brackets listed at the start of the lines in #22. Something like:

ado uninstall [16]