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MathGroup Archive 2004

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Re: Re: KS Analysis In Mathematica

  • To: mathgroup at smc.vnet.net
  • Subject: [mg49321] Re: [mg49309] Re: KS Analysis In Mathematica
  • From: Mark Coleman <mark at markscoleman.com>
  • Date: Wed, 14 Jul 2004 07:29:26 -0400 (EDT)
  • References: <cctadj$c0u$1@smc.vnet.net> <200407130832.EAA09623@smc.vnet.net>
  • Sender: owner-wri-mathgroup at wolfram.com

Doug,

If this is of interest, here is code for the Bera-Jarque test of 
normality. The module takes the data to be tested as an argument and 
returns a two-element list consisting of the Bera-Jarque statistic and 
it's p-value.

Needs["Statistics`DescriptiveStatistics`"];
Clear[beraJarque];
beraJarque[d_] := Module[{s, k, n, bj, bjsig},
     n = Length[d];
     s = Skewness[d];
     k = KurtosisExcess[d];
     bj = (n/6)*s^2 + (n/24)*k^2;
     bjsig = 1.0 - CDF[ChiSquareDistribution[2], bj];
     {bj, bjsig}
     ]

Regards,

Mark




On Jul 13, 2004, at 4:32 AM, Doug wrote:

> The links to the stats packages don't work....and neither does the 
> contact
> info to these people
> ???
>
> Doug
> "Christos Argyropoulos MD" <chrisarg at medscape.com> wrote in message
> news:cctadj$c0u$1 at smc.vnet.net...
>> Hi,
>> Try the following url
>> http://www.verbeia.com/mathematica/mathecon/othercode.html
>> if you are after for a "Normality" test and other goodies.
>> Alternatively try the following Mathematica Code:
>> -------------------------------------------------------------
>> Needs["Statistics`DescriptiveStatistics`"];
>> Needs["Statistics`DataManipulation`"];
>> Needs["Statistics`ContinuousDistributions`"];
>> Needs["Statistics`DescriptiveStatistics`"];
>> Needs["Statistics`ConfidenceIntervals`"];
>> Needs["Statistics`MultiDescriptiveStatistics`"];
>> Q[s_] := Module[{r}, Sum[(r - s)^r*(x^r)/r!, {r, 0, Floor[s]}]]
>> F[s_, m_] := Normal[Series[Simplify[(Q[s]^2)/Q[2*s]], {x, 0, m}]]
>> Kolmogorov[d_, m_] := Min[N[Abs[Coefficient[F[m*d, m], x, m]*m!/
>> (m^m)]], 1]
>> Lillefors[y_List] := Module[{stand, quant,
>>        kolm}, stand = Standardize[y]; quant = Transpose[QuantileForm
>> [stand]];
>>     kolm = N[Max[Abs[quant[[1]] -
>>  Map[CDF[NormalDistribution[0, 1], #] &, quant[[2]]]]]]]
>> -------------------------------------------------------------
>> Kolmogorov[d,m] gives the Probability of the Kolmogorov Smirnov Test
>> when the test statistic value is d and the sample tested is of size m.
>> If you want to test whether a list of observations has come from a
>> Normal Distribution with unknow mean and variance, use the function
>> Lillefors[obs] which calculates the P-value based on the Lillefors
>> modification of the KS statistic.
>> Cheers
>> Christos Argyropoulos
>>
>>
>>
>>
>> Sent by Medscape Mail: Free Portable E-mail for Professionals on the 
>> Move
>> http://www.medscape.com
>>
>
>
>


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