st: How can I prevent -simulate- from stopping after non-convergence?

[Jonathan Beck <beck@wz-berlin.de>]

Dear Listeners,

using Stata 8.2 (just updated) on Win XP, I attempt to

. simulate "simPTM1" bM=_b[M], reps(20)

The program simPTM1 contains an -nl- estimation and I get the following 
error whenever the estimation lacks convergence:

---snip
convergence not achieved

command -> simPTM1
an error occurred when command was executed on original dataset
please rerun and specify the trace option to see a trace of the commands
executed
r(430);
---snip

I would rather like that -simulate- posts a missing value for bM in that
round and continues with the next round of replication. Actually, that
is what Jeff Pitblado promised in a previous Statalist response:
http://www.hsph.harvard.edu/cgi-bin/lwgate/STATALIST/archives/statalist.0401/date/article-461.html

Any hints?

The complete do-file is appended below.
(Any advise on the -nl- program is also appreciated.)

Many thanks
Jonathan

----begin do-file
version 8.2
clear
set mem 100m
set matsize 800
set more off

program drop _all

program nlPTM1SalR
        version 8.2
        if "`1'" == "?" {
            global S_1 "NLS estimation of PTM1 for period sales /*
                        */ (constrained parameters)"
            global S_1 "EM ETH EP EQ"
            local exp "[`e(wtype)' `e(wexp)']"
            global EM=6.8
            global ETH=-.4
            global EP=-1.7
            global EQ=-3
            exit
        }
        replace
`1'=exp($EM)*((exp($ETH)/(1+exp($ETH)))*(exp(-exp($EP)*(time-1))-exp(-exp($EP)*time)+(exp(-exp($EQ)*time)*exp(exp($EQ)/exp($EP)*(1-exp(-exp($EP)*time))))-(exp(-exp($EQ)*(time-1))*exp(exp($EQ)/exp($EP)*(1-exp(-exp($EP)*(time-1))))))+(exp(-exp($EQ)*(time-1))*exp(exp($EQ)/exp($EP)*(1-exp(-exp($EP)*(time-1)))))-(exp(-exp($EQ)*time)*exp(exp($EQ)/exp($EP)*(1-exp(-exp($EP)*time)))))
end

program simPTM1, eclass
  drop _all
  set more off
  set obs 20
  gen time=_n-1
  /* set parameters to be estimated */
  gen m=1000
  gen type1Sh=.4
  gen q=.5
  gen p=.1
  /* generate dependent variable according to nonlinear model */
  gen
CumSales=m*(1-type1Sh*(exp(-p*time)-(exp(-q*time)*exp(q/p*(1-exp(-p*time)))))-(exp(-q*time)*exp(q/p*(1-exp(-p*time)))))
  gen Sales=CumSales[_n]-CumSales[_n-1]
  replace Sales=CumSales if time==1
  /* generate shock and dependent variable which enters estimation*/
  gen shock1=1+0.1*invnorm(uniform())
  gen RealSales=Sales*shock1
  /* estimate model*/
  nl PTM1SalR RealSales
  scalar define bM=_b[EM]
  scalar define bP=_b[EP]
  scalar define bQ=_b[EQ]
  scalar define bTH=_b[ETH]
  scalar define rmse=e(rmse)
  scalar define rsq=e(r2)
  scalar define iter=e(ic)
  scalar define Dconv=e(converge)
end

set seed 8

simulate "simPTM1" bM=_b[EM] bTH=_b[ETH] bP=_b[EP] bQ=_b[EQ] /*
      */ rmse=e(rmse) rsq=e(r2) iter=e(ic) Dconv=e(converge), reps(20)
descr
summarize, detail
----end do-file




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