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From |
"Victor M. Zammit" <vmz@vol.net.mt> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Re: Memory |

Date |
Thu, 13 Nov 2008 18:21:35 +0100 |

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/ > > > * > * 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/ > * * 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:*"Austin Nichols" <austinnichols@gmail.com>

**st: D. Time series operator***From:*Diana Eastman <deastman@gma-us.com>

**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>

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