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Thanks Howard,
This very much looks like the list of Z-scores I had seen before, as
mentioned in my mail yesterday !
Still, your function is equal to Excel's NORMSINV(p) function which I
already got. Iow, I have functions to translate a standardized z-
score into a prob and vice versa. Using the A&S mentioned below, I
can get probs for values where Mu and SD are not zero, resp 1.
However, they do not match XL's values.
Thx anyway, I'll continue digging.
PS
--- In amibroker@xxxxxxxxxxxxxxx, "Howard B" <howardbandy@xxx> wrote:
>
> Hi --
>
> How will you be using the distribution?
>
> How much accuracy do you need?
>
> Here is afl code that will initialize an array with the Cumulative
> Distribution Function of the Normal Distribution.
>
> //---------------------------
>
> // InitializeNormalCDF.afl
> //
> function InitializeNormalCDF()
> // Initialize the array that holds the coefficients
> // for the Normal Cumulative Distribution function.
> {
> NormCDF[0] = -3.090;
> NormCDF[1] = -2.326;
> NormCDF[2] = -2.053;
> NormCDF[3] = -1.881;
> NormCDF[4] = -1.751;
> NormCDF[5] = -1.645;
> NormCDF[6] = -1.555;
> NormCDF[7] = -1.476;
> NormCDF[8] = -1.405;
> NormCDF[9] = -1.341;
> NormCDF[10] = -1.282;
> NormCDF[11] = -1.227;
> NormCDF[12] = -1.175;
> NormCDF[13] = -1.126;
> NormCDF[14] = -1.080;
> NormCDF[15] = -1.036;
> NormCDF[16] = -0.994;
> NormCDF[17] = -0.954;
> NormCDF[18] = -0.915;
> NormCDF[19] = -0.878;
> NormCDF[20] = -0.842;
> NormCDF[21] = -0.806;
> NormCDF[22] = -0.772;
> NormCDF[23] = -0.739;
> NormCDF[24] = -0.706;
> NormCDF[25] = -0.674;
> NormCDF[26] = -0.643;
> NormCDF[27] = -0.613;
> NormCDF[28] = -0.583;
> NormCDF[29] = -0.553;
> NormCDF[30] = -0.524;
> NormCDF[31] = -0.496;
> NormCDF[32] = -0.468;
> NormCDF[33] = -0.440;
> NormCDF[34] = -0.412;
> NormCDF[35] = -0.385;
> NormCDF[36] = -0.358;
> NormCDF[37] = -0.332;
> NormCDF[38] = -0.305;
> NormCDF[39] = -0.279;
> NormCDF[40] = -0.253;
> NormCDF[41] = -0.228;
> NormCDF[42] = -0.202;
> NormCDF[43] = -0.176;
> NormCDF[44] = -0.151;
> NormCDF[45] = -0.126;
> NormCDF[46] = -0.100;
> NormCDF[47] = -0.075;
> NormCDF[48] = -0.050;
> NormCDF[49] = -0.025;
> NormCDF[50] = 0.000;
> NormCDF[51] = 0.025;
> NormCDF[52] = 0.050;
> NormCDF[53] = 0.075;
> NormCDF[54] = 0.100;
> NormCDF[55] = 0.126;
> NormCDF[56] = 0.151;
> NormCDF[57] = 0.176;
> NormCDF[58] = 0.202;
> NormCDF[59] = 0.228;
> NormCDF[60] = 0.253;
> NormCDF[61] = 0.279;
> NormCDF[62] = 0.305;
> NormCDF[63] = 0.332;
> NormCDF[64] = 0.358;
> NormCDF[65] = 0.385;
> NormCDF[66] = 0.412;
> NormCDF[67] = 0.440;
> NormCDF[68] = 0.468;
> NormCDF[69] = 0.496;
> NormCDF[70] = 0.524;
> NormCDF[71] = 0.553;
> NormCDF[72] = 0.583;
> NormCDF[73] = 0.613;
> NormCDF[74] = 0.643;
> NormCDF[75] = 0.674;
> NormCDF[76] = 0.706;
> NormCDF[77] = 0.739;
> NormCDF[78] = 0.772;
> NormCDF[79] = 0.806;
> NormCDF[80] = 0.842;
> NormCDF[81] = 0.878;
> NormCDF[82] = 0.915;
> NormCDF[83] = 0.954;
> NormCDF[84] = 0.994;
> NormCDF[85] = 1.036;
> NormCDF[86] = 1.080;
> NormCDF[87] = 1.126;
> NormCDF[88] = 1.175;
> NormCDF[89] = 1.227;
> NormCDF[90] = 1.281;
> NormCDF[91] = 1.341;
> NormCDF[92] = 1.405;
> NormCDF[93] = 1.476;
> NormCDF[94] = 1.555;
> NormCDF[95] = 1.645;
> NormCDF[96] = 1.751;
> NormCDF[97] = 1.881;
> NormCDF[98] = 2.054;
> NormCDF[99] = 2.326;
> NormCDF[100] = 3.090;
> return(Null);
> }
> //Figure 22.5 Initialization of CDF
> //--------------------------
>
> A fairly detailed discussion about how to use it, including an
example, is
> on pages 295 through 305 of my book -- Quantitative Trading Systems.
>
> Thanks,
> Howard
> www.quantitativetradingsystems.com
>
>
>
>
> On 5/30/07, vlanschot <vlanschot@xxx> wrote:
> >
> > I have various functions for normal distributions, but for some
reason
> > none seem to be able to replicate Excel's NORMDIST
(x,mean,stdev,TRUE).
> >
> > I've applied the Abramowitz & Stegun approximation to calculate
the
> > cumulative normal function. However, the pdf agrees with Excel's
> > NORMDIST(x,mean,stdev,FALSE), but the cdf does not match its
NORMDIST
> > (x,mean,stdev,TRUE).
> >
> > I did read there have been criticisms expressed as to the
accuracy of
> > XL's approximations, but doubt this is applicable in this case.
> >
> > Any suggestions appreciated.
> >
> > PS
> >
> >
> >
>
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