I am fairly new to Stata programming but would like to perform a
simulation whereby I create a dataset containing means and variances of
1000-observation samples from a log-normal distribution with a given
mean and standard deviation. I would like to output the 1000 generated
mean and standard deviations pairs (or doublets) and plot these as (x,y)
coordinates . Eventually, I would also like the output to contain the
skewness and kurtosis and understand that, to do this, I would need to
use the "summarize, detail" command and I could do this using
incorporating r(skewness) and r(kurtosis) as output requests into the
program.
As a first step in this process, I thought I would try out an example in
Stata's on-line help function and see if it worked. I typed "help
simulate" into Stata and copied a sample program from there into Stata.
When I did this, however, Stata told me that there was an "error when
command executed on original dataset under version 8.1 control r(199);"
As this was a sample command taken directly from the Stata on-line help
files, I was puzzled. I thought that it might help to add in "version
8.0" into the program as line 1 (so that it would understand that it was
supposed to work under the the 8.0 version of Stata), but this didn't
work either and Stata came back with the same error.
Does anyone know what needs to be done to modify programs if the 8.1
version of Stata will now longer accept them? Or if I am doing
something wrong? I am using Stata 8.1 born 01 July 2003. I have
excerpted below my sample program which was copied directly from a
sample program provided under Stata's on-line help function as well as
Stata's response about v.8.1 control.
. about
Intercooled Stata 8.1 for Windows
Born 01 Jul 2003
Copyright (C) 1985-2003
Total physical memory: 259992 KB
Available physical memory: 4224 KB
program define lnsim, rclass
1. syntax [, obs(integer 1) mu(real 0) sigma(real 1)]
2. drop _all
3. set obs `obs'
4. temvar z
5. gen `z'=exp(`mu' + `sigma' * invnorm(uniform()))
6. summarize `z'
7. return scalar mean=r(mean)
8. return scalar Var = r(Var)
9. end
. simulate "lnsim, obs(100)" mean=r(mean) var=r(Var), reps(10000)
command -> lnsim , obs(100)
error when command executed on original dataset under version 8.1
control
r(199);
. simulate "lnsim, obs(50) mu(-3) sigma(7)" mean=r(mean) var=r(Var),
reps(10000)
command -> lnsim , obs(50) mu(-3) sigma(7)
error when command executed on original dataset under version 8.1
control
r(199);
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