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From |
Francesco <k7br@gmx.fr> |

To |
njcoxstata@gmail.com |

Subject |
Re: st: algorithmic question : running sum and computations |

Date |
Fri, 17 Aug 2012 14:45:43 +0200 |

Actually Nick there is only a slight problem : dates could be repeated for the same individual AND the same product : for example there could be several round trips during the same day for the same product... In that case I would consider that there are as many delta_Date equal to zero as different round trips during the day for a particular product... My apologies I did not think of this particular and important case... Could the trick egen panelid = group(id product) be adapted in that case ? Many thanks Best Regards On 17 August 2012 13:58, Francesco <k7br@gmx.fr> wrote: > Many, Many thanks Nick and Scott for your kind and very precise > answers! Spells is indeed what I needed ;-) > > > On 17 August 2012 13:43, Nick Cox <njcoxstata@gmail.com> wrote: >> Using your data as a sandpit >> >> . clear >> >> . input id date str1 product quantity >> >> id date product quantity >> 1. 1 1 A 10 >> 2. 1 2 A -10 >> 3. 1 1 B 100 >> 4. 1 2 B -50 >> 5. 1 4 C 15 >> 6. 1 8 C 100 >> 7. 1 9 C -115 >> 8. 1 10 C 10 >> 9. 1 11 C -10 >> 10. end >> >> it seems that we are interested in the length of time it takes for >> cumulative quantity to return to 0. -sum()- is there for cumulative >> sums: >> >> . bysort id product (date) : gen cumq = sum(q) >> >> In one jargon, we are interested in "spells" defined by the fact that >> they end in 0s for cumulative quantity. In Stata it is easiest to work >> with initial conditions defining spells, so we negate the date >> variable to reverse time: >> >> . gen negdate = -date >> >> As dates can be repeated for the same individual, treating data as >> panel data requires another fiction, that panels are defined by >> individuals and products: >> >> . egen panelid = group(id product) >> >> Now we can -tsset- the data: >> >> . tsset panelid negdate >> panel variable: panelid (unbalanced) >> time variable: negdate, -11 to -1, but with a gap >> delta: 1 unit >> >> -tsspell- from SSC, which you must install, is a tool for handling >> spells. It requires -tsset- data; the great benefit of that is that it >> handles panels automatically. (In fact almost all the credit belongs >> to StataCorp.) Here the criterion is that a spell is defined by >> starting with -cumq == 0- >> >> . tsspell, fcond(cumq == 0) >> >> -tsspell- creates three variables with names by default _spell _seq >> _end. _end is especially useful: it is an indicator variable for end >> of spells (beginning of spells when time is reversed). You can read >> more in the help for -tsspell-. >> >> . sort id product date >> >> . l id product date cumq _* >> >> +---------------------------------------------------+ >> | id product date cumq _spell _seq _end | >> |---------------------------------------------------| >> 1. | 1 A 1 10 1 2 1 | >> 2. | 1 A 2 0 1 1 0 | >> 3. | 1 B 1 100 0 0 0 | >> 4. | 1 B 2 50 0 0 0 | >> 5. | 1 C 4 15 2 3 1 | >> |---------------------------------------------------| >> 6. | 1 C 8 115 2 2 0 | >> 7. | 1 C 9 0 2 1 0 | >> 8. | 1 C 10 10 1 2 1 | >> 9. | 1 C 11 0 1 1 0 | >> +---------------------------------------------------+ >> >> You want the mean length of completed spells. Completed spells are >> tagged by _end == 1 or cumq == 0 >> >> . egen meanlength = mean(_seq/ _end), by(id) >> >> This is my favourite division trick: _seq / _end is _seq if _end is 1 >> and missing if _end is 0; missings are ignored by -egen-'s -mean()- >> function, so you get the mean length for each individual. It is >> repeated for each observation for each individual so you could go >> >> . egen tag = tag(id) >> . l id meanlength if tag >> >> I wrote a tutorial on spells. >> >> SJ-7-2 dm0029 . . . . . . . . . . . . . . Speaking Stata: Identifying spells >> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox >> Q2/07 SJ 7(2):249--265 (no commands) >> shows how to handle spells with complete control over >> spell specification >> >> which is accessible at >> http://www.stata-journal.com/sjpdf.html?articlenum=dm0029 >> >> Its principles underlie -tsspell-, but -tsspell- is not even >> mentioned, for which there is a mundane explanation. Explaining some >> basics as clearly and carefully as I could produced a paper that was >> already long and detailed, and adding detail on -tsspell- would just >> have made that worse. >> >> For more on spells, see Rowling (1997, 1998, 1999, etc.). >> >> Nick >> >> On Fri, Aug 17, 2012 at 11:30 AM, Francesco <cariboupad@gmx.fr> wrote: >>> Dear Statalist, >>> >>> I am stuck with a little algorithmic problem and I cannot find an >>> simple (or elegant) solution... >>> >>> I have a panel dataset as (date in days) : >>> >>> ID DATE PRODUCT QUANTITY >>> 1 1 A 10 >>> 1 2 A -10 >>> >>> 1 1 B 100 >>> 1 2 B -50 >>> >>> 1 4 C 15 >>> 1 8 C 100 >>> 1 9 C -115 >>> >>> 1 10 C 10 >>> 1 11 C -10 >>> >>> >>> >>> and I would like to know the average time (in days) it takes for an >>> individual in order to complete a full round trip (the variation in >>> quantity is zero) >>> For example, for the first id we can see that there we have >>> >>> ID PRODUCT delta_DATE delta_QUANTITY >>> 1 A 1=2-1 0=10-10 >>> 1 C 5=4-9 0=15+100-115 >>> 1 C 1=11-10 0=10-10 >>> >>> so on average individual 1 takes (1+5+1)/3=2.3 days to complete a full >>> round trip. Indeed I can discard product B because there is no round >>> trip, that is 100-50 is not equal to zero. >>> >>> My question is therefore ... do you have an idea obtain this simply in >>> Stata ? I have to average across thousands of individuals... :) >> * >> * 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: algorithmic question : running sum and computations***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: algorithmic question : running sum and computations***From:*Francesco <cariboupad@gmx.fr>

**Re: st: algorithmic question : running sum and computations***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: algorithmic question : running sum and computations***From:*Francesco <k7br@gmx.fr>

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