Thanks for your replies Martin & Nick.
Martin: My question was actually simpler - was my procedure correct?
That is, should the data be standardised by an estimate of the scale
before using the Kolmogorov-Smirnov procedure or is that not
necessary?
Also, from the help file for chi2fit by Stas Kolenikov I could not
figure out how to implement it for a t-distribution. Any help will be
appreciated.
Nick: I am particularly interested in deviation from a t-distribution.
My data is almost certainly non-normal. I agree about the merits of
plotting it, but am not aware of any tools for my particular case. Any
ideas?
Thanks.
On Mon, Sep 28, 2009 at 2:46 PM, Martin Weiss <[email protected]> wrote:
>
> <>
>
> As Maarten said back in the day
> (http://www.stata.com/meeting/snasug08/buis_MLBsimulate.zip), you have to
> -simulate- these things to make up your own mind whether you are on the
> right path:
>
>
>
> *************
> //drop it beforehand
> capt prog drop sim
>
> //define the program
> program define sim
> version 11
> syntax [, df(integer 5) obs(real 10000)]
> drop _all
> set obs `obs'
> tempvar z
> gen `z' = rt(`df')
> ksmirnov `z' = 1-ttail(`df',`z')
> end
>
> //simulate it!
> simulate pcor=r(p_cor), /*
> */ reps(1000): sim
>
> //result?
> qui cou if pcor<0.05
> di in red "Rejections: `r(N)', " /*
> */ "for a rate of: " r(N)/c(N)
> *************
>
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von tzygmund
> mcfarlane
> Gesendet: Montag, 28. September 2009 13:47
> An: [email protected]
> Betreff: st: ksmirnov
>
> I am trying to test if a series is t-distributed with (say) 6 degrees
> of freedom using a Kolmogorov-Smirnov test. Is this the right way to
> do it?
>
> webuse wpi1
> g returns = D.ln_wpi
> ksmirnov returns = 1-ttail(6, returns)
>
> thanks.
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