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From |
"Austin Nichols" <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Re: Memory |

Date |
Thu, 13 Nov 2008 13:27:30 -0500 |

Victor M. Zammit <vmz@vol.net.mt>: I don't understand this reply at all. Did you try the simulation approach? It takes very little memory: Contains data from \t.dta obs: 100,000 simulate: makez vars: 1 13 Nov 2008 11:04 size: 1,200,000 (99.9% of memory free) g d=0 replace d=1.31 if t>1.31 replace d=1.697 if t>1.697 replace d=2.042 if t>2.042 replace d=2.457 if t>2.457 replace d=2.75 if t>2.75 tab d d | Freq. Percent Cum. ------------+----------------------------------- 0 | 90,017 90.02 90.02 1.31 | 4,974 4.97 94.99 1.697 | 2,441 2.44 97.43 2.042 | 1,523 1.52 98.95 2.457 | 552 0.55 99.51 2.75 | 493 0.49 100.00 ------------+----------------------------------- Total | 100,000 100.00 _pctile t, nq(100) ret li r(r99) = 2.475399255752564 r(r95) = 1.697941184043884 r(r90) = 1.30941379070282 On Thu, Nov 13, 2008 at 12:21 PM, Victor M. Zammit <vmz@vol.net.mt> wrote: > t-table.I understand that you need a number of random tries ,much bigger > than that of forty thousand,to come to convergence.So I was wondering if > that that constraint with memory ,could be handled. > > > ----- Original Message ----- > From: "Austin Nichols" <austinnichols@gmail.com> > To: <statalist@hsphsun2.harvard.edu> > Sent: Thursday, November 13, 2008 4:09 PM > Subject: Re: st: Re: Memory > > >> Victor M. Zammit: >> I also don't understand the point of this exercise--but you should >> read -help simul- and try e.g. >> >> prog makez, rclass >> syntax [, obs(integer 31)] >> clear >> set obs `obs' >> gen a = invnorm(uniform()) >> ttest a=0 >> return scalar t=r(t) >> end >> simul, reps(100000) seed(123): makez >> >> >> On Thu, Nov 13, 2008 at 9:56 AM, Nick Cox <n.j.cox@durham.ac.uk> wrote: >> > I still don't understand what you are trying to do. But I can comment on >> > your code. >> > >> > You are looping round 40,000 times and writing a single result to 40,000 >> > data files. Then you are looping round to put all those 40,000 data >> > files in one. >> > >> > I'd do that directly this way using just one extra file: >> > >> > clear >> > set obs 31 >> > gen a = . >> > tempname out >> > postfile `out' t using myresults.dta >> > qui forval i = 1/40000 { >> > replace a = invnorm(uniform()) >> > ttest a = 0 >> > post `out' (r(t)) >> > } >> > postclose `out' >> > >> > I still doubt 40,000 is anywhere big enough to get an answer. >> > >> > Nick >> > n.j.cox@durham.ac.uk >> > >> > Victor M. Zammit >> > >> > * a} The data that I have is from generating random samples of whatever >> > size,in this case of size 31,from a normally distributed,infinitely >> > large, >> > population; ie >> > >> > local i = 1 >> > >> > while `i'<= 40000 { >> > >> > drop _all >> > >> > set obs 31 >> > >> > gen a = invnorm(uniform()) >> > >> > qui ttest a = 0 >> > >> > replace a = r(t) in 1 >> > >> > keep in 1 >> > >> > save a`i',replace >> > >> > local i = `i'+1 >> > >> > } >> > >> > * I use 40000 due to memory constraint.Appending the a[i]'s together >> > gives >> > me a variable of 40000 observations ,ie >> > >> > use a1,clear >> > >> > local i = 2 >> > >> > while `i'<= 40000 { >> > >> > append using a`i'.dta >> > >> > local i = `i'+1 >> > >> > } >> > >> > save ais40000,replace >> > >> > * b) From ais40000.dta I get the density <= 1.31, presumably to get the >> > density of 90% , <= 1.697 to get the density of 95% etc etc,according to >> > the >> > official ttable, ie >> > >> > capture program drop density >> > >> > program define density >> > >> > use ais40000,clear >> > >> > count if a<= `1' >> > >> > di " density >=" "`1'" " = " r(N)/40000 >> > >> > end >> > >> > density 1.31 >> > >> > density 1.697 >> > >> > density 2.042 >> > >> > density 2.457 >> > >> > density 2.75 >> > >> > * For smaller degrees of freedom,the discrepancy is much higher.I would >> > like >> > to know how if it is at all possible to resolve memory constraint . * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Re: Memory***From:*"Victor M. Zammit" <vmz@vol.net.mt>

**References**:**Re: st: Re: Memory***From:*"Victor M. Zammit" <vmz@vol.net.mt>

**RE: st: Re: Memory***From:*"Kieran McCaul" <kamccaul@meddent.uwa.edu.au>

**Re: st: Re: Memory***From:*"Victor M. Zammit" <vmz@vol.net.mt>

**RE: st: Re: Memory***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: Re: Memory***From:*"Austin Nichols" <austinnichols@gmail.com>

**Re: st: Re: Memory***From:*"Victor M. Zammit" <vmz@vol.net.mt>

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