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Re: st: distribution test


From   Maarten Buis <maartenlbuis@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: distribution test
Date   Tue, 30 Aug 2011 12:19:55 +0200

On Tue, Aug 30, 2011 at 11:13 AM, Nick Cox wrote:
> There is a direct method to check for fit to an exponential
> distribution: a quantile-quantile plot. See -qexp- (SSC) and/or
>
> SJ-7-2  gr0027  . .  Stata tip 47: Quantile-quantile plots without programming
>        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J. Cox
>        Q2/07   SJ 7(2):275--279                                 (no commands)
>        tip on producing various quantile-quantile (Q-Q) plots
>
> on how to do it for yourself. The latter is directly accessible at

I like to use estimated coefficients for computing the values on the
x-axis, as that way the graph should be square and the reference line
is the 45 degree line. Moreover,I like to supplement such a
quantile-quantile plot with several random draws from the assumed
distribution. This gives me an idea of how much deviation from the
theoretical distribution I might reasonably expect. Below is an
example of how I would do that.

*--------------------- begin example --------------------
// create some expnential data
local lambda = 2
drop _all
set obs 500
gen y = -1/`lambda'*ln(1-runiform())
label var y "observed"

// estimate parameter
sum y, meanonly
local lambdahat = 1/r(mean)
di as txt "ML estimate of lambda is: " ///
   as result `lambdahat'

// will use that later for computing the range of the graph
local max = r(max)

// As discussed in: Nicholas J. Cox (2007) Stata tip 47:
// Quantile-quantile plots without programming. The Stata
// Journal, 7(2): 275--279.
egen rank = rank(y)
egen n = count(y)
gen pp = (rank - 0.5) / n
gen exponential = -1/`lambdahat'*ln(1 - pp)

// will use that to compute the range of the reference line
sum exponential, meanonly
local reflinerange "range(0 `r(max)')"

// create 20 random variables assuming the model is correct
forvalues i = 1/20 {
	gen y`i' = -1/`lambdahat'*ln(1-runiform())
	egen rank`i' = rank(y`i')
	egen n`i' = count(y`i')
	gen pp`i' = (rank`i' - 0.5) / n`i'
	gen exponential`i' = -1/`lambdahat'*ln(1 - pp`i')
	drop rank`i' n`i'  pp`i'
	#delim ;
	local gr `"`gr' || line y`i' exponential`i',
	            sort lstyle(solid) lcolor(gs12)"' ;
	#delim cr
	sum y`i', meanonly
	local max = max(`r(max)', `max')
}

// compute nice axis labels
_natscale 0 `max' 5
local lab "lab(`r(min)'(`r(delta)')`r(max)')"

// make sure the graph is square
local range "scale(range(0 `max'))"

// use var label for y-axis title when present
if `"`: var label y'"' != "" {
	local ytitle `"ytitle(`"`: var label y'"')"'
}
else {
	local ytitle `"ytitle(y)"'
}

// create the graph
twoway `gr'                            || ///
       scatter y exponential,             ///
       y`lab' x`lab' y`range' x`range'    ///
       aspect(1) msymbol(oh)           || ///
       function reference = x,            ///
       `reflinerange' lstyle(solid)       ///
       legend(order( 1 "samples" 21 22 )) ///
       xtitle(exponential distribution)   ///
       `ytitle'
*---------------------- end example ---------------------
(For more on examples I sent to the Statalist see:
http://www.maartenbuis.nl/example_faq )

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany


http://www.maartenbuis.nl
--------------------------

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