RE: [R] help on ks.test

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From: Trenkler, Dietrich (dtrenkler@nts6.oec.uni-osnabrueck.de)
Date: Fri 07 May 2004 - 01:01:00 EST


Message-id: <FB75CFC167F3D311B11D00A0CC20FB0E88546B@nts7.oec.Uni-Osnabrueck.DE>


> -----Original Message-----
> From: Peter Dalgaard
> Sent: Thursday, May 06, 2004 4:32 PM
> To: Janete Borges
> Cc: r-help@stat.math.ethz.ch
> Subject: Re: [R] help on ks.test
>
> "Janete Borges" <janeteborges@gmx.net> writes:
>
> > Dear All
> >
> > I need to test the goodness-of-fit of a (Negative) Exponential
> Distribution
> > to a dataset. The parameter of the distribution is unknown. What is the
> > appropriate test to do? I've tried the ks.test, although I think this
> > isn't the appropriate one, as I don't know the population parameter.
> > Can anybody help me?
> >
> > Thanks in advance,
> > Janete
>
> The bias of the K-S test with estimated parameters is well known to be
> substantial, but I haven't heard about correction terms except (I
> think) for the normal distribution.
         
        [Dietrich Trenkler] There is a Lilliefors-version of the KS-test
        for the exponential distribution. See e.g.

        @ARTICLE{Lilliefors69a,
          author = {H. W. Lilliefors},
          year = 1969,
          title = {On the {K}olmogorov-{S}mirnov Test for Exponential
                   Distribution with Mean Unknown Variance Unknown},
          journal = {Journal of the American Statistical Association},
          volume = 64,
          pages = {387--389},
          keywords = {Lilliefors Test for Exponentiality; Goodness-of-Fit;
                     Kolmogorov's Test}
        }

         or

        @ARTICLE{Mason86,
          author = {Andrew L. Mason and C.B. Bell},
          year = 1986,
          title = {New {L}illiefors and {S}rinivasan Tables with
Applications},
          journal = {Communications in Statistics, Part B--Simulation and
Computation},
          volume = 15,
          pages = {451--477},
          comment = {BIB 2},
          keywords = {Lilliefors Test; Goodness-of-Fit; Simulation}
        }
         
        HTH

        Let me stress that the KS-test may not be very powerful.

         Dietrich

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