comp.lang.idl-pvwave archive: archive » Re: Resampling from cumulative probability distribution

Home » Public Forums » archive » Re: Resampling from cumulative probability distribution

Show: Today's Messages :: Show Polls :: Message Navigator
E-mail to friend

Re: Resampling from cumulative probability distribution [message #58340 is a reply to message #58337]

Sun, 27 January 2008 12:38

jschwab@gmail.com
Messages: 30
Registered: December 2006

Member

I didn't test it, but if I understand what you're doing, the following
code should work.

Cheers,
Josiah
--

function get_bootstrap_pdf, np, cdf

zz = randomu(S, np) ; np is the number of samples

n_cdf = n_elements(cdf) ; ncdf is the number of points in the cdf

;; the next step finds where each zz falls in the cdf,
;; which is of course monotonically nondecreasing

zz_locs = value_locate(cdf, zz)

;; value locate returns a list of indices of the element such that
;; cdf[indices[j]] < zz[j] < cdf[indices[j]+1]
;; read the documentation if that's too terse an explanation

;; since the indices are evenly spaced, unlike the cdf values
;;(which is presumably why you couldn't just use histogram in the
;; first place) we can use the histogram command

;; the number of zeros, that is the first element of zz_hist,
;; tells you how many zz values fell between cdf[0] and cdf[1]

zz_hist = histogram(zz_locs, min = 0 , max = ncdf - 2, binsize = 1)

;; now just divide by the total of zz_hist, which presumably is np

zz_norm = zz_hist / nb

return, zz_norm

end

On Jan 26, 9:09 am, Klemens <jokulhl...@web.de> wrote:
> Hallo together,
>
> I am computing a bootstrap analysis where the resampling routine from
> a cumulative probability distribution needs the most cpu time. May be
> you have some ideas how to eliminate the loop and speed up the
> routine ...
>
> function get_bootstrap_pdf, np, cdf
>
> zz = randomu(S, np) ; np is the number of
> samples
>
> cdfa = cdf[0:n_elements(cdf)-2] ; cdf is the cumulative
> probability distribution
> cdfb = cdf[1:n_elements(cdf)-1]
>
> b = fltarr(n_elements(cdf)) ; b will be the
> resampled distribution
> b[*] = 0.00
>
> for i = 0, n_elements(cdf)-2 do begin ;
> loop through all bins
> index = where((zz ge cdfa[i]) and (zz lt cdfb[i]))
> if (max(index) ge 0) then begin
> b[i] = n_elements(index)
> endif else begin
> b[i] = 0.00
> endelse
> endfor
>
> total_b = total(b)
> b = b / total(b)
>
> return, b
>
> end
>
> Thanks for your help in advance !
>
> Klemens

Report message to a moderator

[Message index]

		Re: Resampling from cumulative probability distribution By: Klemens on Sun, 27 January 2008 23:21
		Re: Resampling from cumulative probability distribution By: jschwab@gmail.com on Sun, 27 January 2008 12:38
		Re: Resampling from cumulative probability distribution By: Klemens on Sat, 26 January 2008 08:42
		Re: Resampling from cumulative probability distribution By: David Fanning on Sat, 26 January 2008 08:19
		Re: Resampling from cumulative probability distribution By: Klemens on Sat, 26 January 2008 07:52
		Re: Resampling from cumulative probability distribution By: David Fanning on Sat, 26 January 2008 06:58

Previous Topic:	IDLdoc 3.0 released
Next Topic:	Overlaying where data

-=] Back to Top [=-

[ Syndicate this forum (XML) ] [

] [

]

Current Time: Fri Oct 10 14:04:46 PDT 2025

Total time taken to generate the page: 0.64115 seconds