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The time is now 5:14 am
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May 2, 2024, 2:36 am
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Happy New Year - The Final Approximation
Published:
Updated:
Happy New Year Folks.
We have finished the study on our Approximation of Random Normal Distribution.
It will work for any range of standard deviation from 0 to ∞ and fractionally very small numbers (i.e. (1/100), (1/1000000), .0001, .00000001, or similar).
Also, those of you that may have noticed, if you use the regular random function in your programming language, you'll see that if the random number goes to zero you'll get an error.
This is because of the natural log in the first half addition, ln().
The function, tan(), goes to zero when y goes to zero and taking the natural log of zero leads to an error.
To fix this problem, your random function needs to fall in the range of greater than zero and less than one.
Below is an example of how to do this in Visual Basic code; this will work in Excel VB as well, modify it to fit your programming language.
______
Function Random() as Double
Dim R as Double
Do
R = Rnd()
Loop Until R <> 0
Random = R
End Function
______
Comments
Even though the sign function, sgn(), goes to zero, it will have an insignificant effect on the outcome.
Function Random() As Double
Dim R As Double
Do
R = Rnd()
Loop Until R <> 0
Random = R
End Function
_____
Function Sinh(a As Double) As Double
Sinh = (Exp(a) - Exp(-1 * a)) / 2
End Function
_____
Function RandomNormal(S As Double) As Double
Dim Pi, y As Double
Pi = 3.14159265358979
y = Random()
RandomNormal = ((2 * S) / Pi) * Log(Tan((Pi * y) / 2)) + Sgn(Rnd() - 0.5) * (2 * Pi + 4 * (Atn(S - 1) - Atn(S + 1))) * Sin(4 * Atn(Sinh(y / 2))) * Exp(-1 * ((y ^ 2) + (Pi ^ 2)) / Pi)
End Function
We're working a Cubic Solution for a Random Sums Distribution.
We have a temporary working solution, but it needs more research, study, and analysis.
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