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Re: st: RE: How to define shortest possible period with 95% of observations


From   Daniel Mueller <mueller@iamo.de>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: How to define shortest possible period with 95% of observations
Date   Thu, 13 May 2010 02:05:28 +0700

Thanks.

In the code below I did my best to think in fire years by defining the peak fire day (these are always unique) as the middle of the year. Then I'd like to place the maximum into a local macro (where I fail miserably in line 2 as Steve rightly pointed out):

qui su no_fire_day
loc yearstart = Day[r(max)] - 183
loc yearend = `yearstart' + 365

My simple question is how I can place the Day where no_fires_day = r(max) into a local macro?

(I ignore leap years for the sake of simplicity..)

Daniel



Nick Cox wrote on 5/12/2010 10:44 PM:
Without looking at this in detail, it seems to me that you might benefit
from thinking in terms of fire years, rather than calendar years,
starting on some day other than January 1.  After all, all sorts of
different sciences, not to mention religions, have years that don't
coincide with conventional Western calendar years: fiscal years, water
years, academic years, etc., etc.

Several pertinent -egen- functions are included in -egenmore- on SSC.

In other words, define the time scale in terms of those fire years; then
Robert's code will probably not need any complicated adjustments.

Nick
n.j.cox@durham.ac.uk

Daniel Mueller

Robert, this works like charm!!! Thanks a bunch for this neat code. Also

thanks to Nick for pointing me to -shorth- which I will certainly
explore in more detail after having sipped through the extensive
reference list.

Using Roberts code I can seamlessly loop over the nine years of data and

generate the shortest fire season per year with 95% of obs. The results
suggested an additional complication.. For some subsets the shortest
possible period likely starts a couple of days before Jan 1st, at the
end of the preceding year.

I tweaked Roberts code a little to loop over years and defined the
middle of a year as the peak fire day. The code runs through, yet sets
the start of the fire season for some subsets to Jan 1st, while my
educated guess is that it should be somewhere around mid to end of
December. Something went wrong, but I can't spot the glitch in the code
below. Can someone please help?

Thanks a lot in advance and best regards,
Daniel


*** start
forv y = `yearfirst'/`yearlast' {

* keep previous year
   if `y' != `yearfirst' {
    keep if Year == `y' | Year == (`y'-1)
   }
   bys Day: g no_fire_day = _N
   qui su no_fire_day

* define year to start 183 days before peak fire day
   loc yearstart = Day[r(max)] - 183
   loc yearend = `yearstart' + 365
   keep if Day>  `yearstart'&  Day<  `yearend' // or with egen->rotate?
   bys Day: keep if _n == _N
   g nobs = _n

* the target is a continuous run that includes 95% of all fires
   sum no_fire_day, meanonly
   scalar target = .95 * r(sum)

   scalar shortlen = .
   gen arun = .
   gen bestrun = .

   * at each pass, create a run that starts at nobs == `i'
   * and identify the nobs where the number of fires>= 95%
   local more 1
   local i = 0
   while `more' {
    local i = `i' + 1
    qui replace arun = sum(no_fire_day * (nobs>= `i'))
    sum nobs if arun>= target, meanonly
    if r(N) == 0 local more 0
    else if (Day[r(min)] - Day[`i'])<  shortlen {
     scalar shortlen = Day[r(min)] - Day[`i']
     qui replace bestrun = arun
     qui replace bestrun = . if nobs>  r(min) | nobs<  `i'
    }
   }
   qui drop if bestrun == .
   drop bestrun arun
   save fires_`y', replace
}
*** end





Robert Picard wrote on 5/11/2010 3:28 AM:
Here is how I would approach this problem. I would do each year
separately; it could be done all at once but it would complicate the
code unnecessarily. If the fire data is one observation per fire, I
would -collapse- it to one observation per day. Each observation would
contain the number of fires that day. The following code will identify
the first instance of the shortest run of days that includes 95% of
fires for the year.

Note that the following code will work, even if there are days without
fires (and thus no observation for that day).

*--------------------------- begin example -----------------------
version 11

* daily fire counts; with some days without fires
clear all
set seed 123
set obs 365
gen day = _n
drop if uniform()<   .1
gen nobs = _n
gen nfires = round(uniform() * 10)

* the target is a continuous run that includes 95% of all fires
sum nfires, meanonly
scalar target = .95 * r(sum)
dis target

scalar shortlen = .
gen arun = .
gen bestrun = .

* at each pass, create a run that starts at nobs == `i'
* and identify the nobs where the number of fires>= 95%
local more 1
local i 0
while `more' {
	local i = `i' + 1
	qui replace arun = sum(nfires * (nobs>=`i'))
	sum nobs if arun>= target, meanonly
	if r(N) == 0 local more 0
	else if (day[r(min)] - day[`i'])<   shortlen {
		scalar shortlen = day[r(min)] - day[`i']
		qui replace bestrun = arun
		qui replace bestrun = . if nobs>   r(min) | nobs<   `i'
	}
}

*--------------------- end example --------------------------


Hope this help,

Robert

On Mon, May 10, 2010 at 6:19 AM, Nick Cox<n.j.cox@durham.ac.uk>
wrote:
I don't think any trick is possible unless you know in advance the
precise distribution, e.g. that it is Gaussian, or exponential, or
whatever, which here is not the case.

So, you need to look at all the possibilities from the interval
starting
at the minimum to the interval starting at the 5% point of the fire
number distribution in each year.

However, this may all be achievable using -shorth- (SSC). Look at the
-proportion()- option, but you would need to -expand- first to get a
separate observation for each fire. If that's not practicable, look
inside the code of -shorth- to get ideas on how to proceed. Note that
no
looping is necessary: the whole problem will reduce to use of -by:-
and
subscripts.

Nick
n.j.cox@durham.ac.uk

Daniel Mueller

I have a strongly unbalanced panel with 100,000 observations (=fire
occurrences per day) that contain between none (no fire) and 3,000
fires

per day for 8 years. The fire events peak in March and April with
about
85-90% of the yearly total.

My question is how I can define the shortest possible continuous
period
of days for each year that contains 95% of all yearly fires. The
length
and width of the periods may slightly differ across the years due to
climate and other parameters.

I am sure there is a neat trick in Stata for this, yet I have not
spotted it. Any suggestions would be appreciated.

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