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Published:
1 - Combinatorial Distribution
Factorial - n! = n * (n -1) * (n - 2) * ... * 3 * 2 * 1 , and 0! = 1
Permutation - P(n,r) = n! / (n - r)!
Combination - C(n,r) = P(n,r) / r!
Combinatorial Distribution - D(n,r,c,z) = C(z - 1, c - 1) * C(n - z, r - c)
n - total number of items
r - number of items in a combinatorial or permutational set
c - column number of the distribution
z - item number of the distribution
2 - Average Rate of Reoccurrence Distribution
Reference - Combinatorial Distribution
Average Rate of Reoccurrence Distribution - m = Ar(n,r,c,z) = C(n,r) / D(n,r,c,z)
3 - Generalized Average Rate of Reoccurrence
Reference - Combinatorial Distribution, Average Rate of Reoccurrence Distribution
Generalized Average Rate of Reoccurrence - m = Ag(n,r) = n / r
n - number of items
r - number of items in a combinatorial set
when c = 1 and z = 1, also a! / (a - 1)! = a
Ag = Ar(n,r,1,1)
Ag = C(n,r) / D(n,r,1,1)
Ag = C(n,r) / (C(1 - 1,1 - 1) * C(n - 1, r - 1))
Ag = C(n,r) / ( 1 * C(n - 1, r - 1))
Ag = C(n,r) / C(n - 1, r - 1)
Ag = (n! / (r! * (n - r)!)) / ((n - 1)! / ((r - 1)! * ((n - 1) - (r - 1))!))
Ag = (n! / (r! * (n - r)!)) / ((n - 1)! / ((r - 1)! * (n - 1 - r + 1)!))
Ag = (n! / (r! * (n - r)!)) / ((n - 1)! / ((r - 1)! * (n - r)!))
Ag = (n! / (r! * (n - r)!)) * ((r - 1)! * (n - r)! / (n - 1)!)
Ag = (n! / (n - 1)!) * ((r - 1)! / r!) * ((n - r)! / (n - r)!)
Ag = (n! / (n - 1)!) * ((r - 1)! / r!) * 1
Ag = (n! / (n - 1)!) * (1 / (r! / (r - 1)!)
Ag = n * (1 / r)
Ag = n / r
4 - Relative Combinatorial Distribution
Reference - Combinatorial Distribution, Average Rate of Reoccurrence Distribution
Relative Combinatorial Distribution - Dr(n,r,c,z,d) = d * (D(n,r,c,z) / C(n,r)) = d / Ar(n,r,c,z)
n - number of items (number of balls)
r - number of items in a combinatorial set (number of picks)
c - column number of the item (position in the pick set; when items in the set are in ascending order)
z - item number (ball number)
d - number of random combinatorial set selections (number of draws)
5 - Discharging Reoccurrence Distribution
Reference - Average Rate of Reoccurrence Distribution, Generalized Average Rate of Reoccurrence
Discharge Reoccurrence - y = (d / m2 ) e -(x / m )
d - total number of draws
m - average rate of reoccurrence
x - draw difference or Dd between two draw occurrences of the same number
y - the approximate frequency of reoccurrence for a given draw difference or Dd for a given draw count d
6 - Potential Reoccurrence Probability
Reference - Discharging Reoccurrence Distribution, Average Rate of Reoccurrence Distribution, Generalized Average Rate of Reoccurrence
Potential Reoccurrence Probability - y = e -(x / m)
x - draw difference or Dd between previous occurrence and next draw number
m - average rate of reoccurrence
y - probability of reoccurrence relative to last occurrence
7 - Potential Occurrence Probability
Reference - Discharging Reoccurrence Distribution, Average Rate of Reoccurrence Distribution, Generalized Average Rate of Reoccurrence, Potential Reoccurrence Probability
Potential Occurrence Probability - y = 1 - e -(x / m)
x - draw difference or Dd between previous occurrence and next draw number
m - average rate of reoccurrence
y - probability of occurrence relative to last occurrence
8 - Half-life of Reoccurrence
Reference - Potential Reoccurrence Probability
Half-life of Reoccurrence - xl = -m ln(1 / 2)
m - average rate of reoccurrence
xl - half-life of reoccurrence
9 - First and Second Order Work Equations
Reference - Potential Reoccurrence Probability, Potential Occurrence Probability, Half-life of Reoccurrence
First Order Work Equation - y = 4 (e -(x / m) - e -(2 x / m) )
Second Order Work Equation - y = 16 (e -(x / m) - 5 e -(2x / m) + 8 e -(3x / m) - 4 e -(4x / m) )
x - draw difference or Dd between last occurrence and some future draw number
m - average rate of reoccurrence
second order region 1 - 0 £ x £ -m ln(1 / 2)
second order region 2 - -m ln(1 / 2) £ x £ ¥
10 - Solution for finding x in the First Order Work Equation
low value for x - x = -m ln((1 + Ö(1 - y)) / 2)
high value for x - x = -m ln((1 - Ö(1 - y)) / 2)
11 - Random Number Transforms - Normal Distribution
Analog - x = ±Ö-2s² ln(1 - y)
Decimal - x = ±(Ö-2s² ln(1 - y) - (s / 2))
Digital - x = ±(Ö-n ln(1 - y) - ((1 / 2) * Ön / 2))
y - random number, 0 £ y < 1
s - standard deviation
n - digital deviation, | x | £ n
x - transformed random number
± - values of x randomly alternate
Analog values are not rounded to any fixed decimal or integer.
Decimal values of x are rounded to nearest fixed decimal place or integer.
Example: 2.591230102345664 is rounded to 2.59.
Digital values of x are rounded to the nearest integer.
Example: 2.591230102345664 is rounded to 3.
Digital limits are valid y samples when | x | £ n.
If | x | > n, then resample y.
Relationship of n and s - n = 2 s² and s = Ön / 2
12 - Random Number Transforms - Reoccurrence Distribution
Reference - Discharging Reoccurrence Distribution
Random Reoccurrence Distribution - x = -m ln(1 - y)
m - average rate of reoccurrence
y - random number, 0 £ y < 1
x as analog - values of x are not rounded to any decimal place value.
x as digital - values of x are converted to the integer part of x.
Ex.1 - 4.129840012394543 is converted to 4
Ex.2 - 2.781992014293572 is converted to 2
valid digital values of x are when x ³ 1
13 - Combinatorial Symmetry - Number Symmetry
Symmetric Number - Sn(n,z) = n - z +1
n - total number of items
z - item number in the set
14 - Combinatorial Symmetry - Column Symmetry
Symmetric Column Number - Sc(r,c) = r - c + 1
r - items per combinatorial set (pick value)
c - column place of the number n referred to in Combinatorial Symmetry - Number Symmetry
15 - Combinatorial Fractalization
C(n, r) = [from z = 1 to z = n - r + 1] å C(n - z, r - 1)
C(n, r) = C(n - 1, r - 1) + C(n - 2, r - 1) + C(n - 3, r - 1) + ... + C(r + 3, r - 1) + C(r + 2, r - 1) + C(r + 1, r - 1) + C(r, r - 1) + C(r - 1, r - 1)
Fractals of C(n, r) - {C(n - 1, r - 1), C(n - 2, r - 1), C(n - 3, r - 1), ... , C(r + 3, r - 1), C(r + 2, r - 1), C(r + 1, r - 1), C(r, r - 1), C(r - 1, r - 1)}
Fractals of C(n, r) - [from z = 1 to z = n - r + 1] y {C(n - z, r - 1)}
16 - Iteration of C(n, r) Fractals
Fractals of C(n - 1, r - 1) - {C(n - 2, r - 2), C(n - 3, r - 2), C(n - 4, r - 2), ... , C(r + 2, r - 2), C(r + 1, r - 2), C(r, r - 2), C(r - 1, r - 2), C(r - 2, r - 2)}
Fractals of C(n - 1, r - 1) - [from z = 1 to z = n - r + 1] y {C(n - z - 1, r - 2)}
Fractals of C(n - 2, r - 1) - {C(n - 3, r - 2), C(n - 4, r - 2), C(n - 5, r - 2), ... , C(r + 2, r - 2), C(r + 1, r - 2), C(r, r - 2), C(r - 1, r - 2), C(r - 2, r - 2)}
Fractals of C(n - 2, r - 1) - [from z = 1 to z = n - r] y {C(n - z - 2, r - 2)}
Fractals of C(n - 3, r - 1) - {C(n - 4, r - 2), C(n - 5, r - 2), C(n - 6, r - 2), ... , C(r + 2, r - 2), C(r + 1, r - 2), C(r, r - 2), C(r - 1, r - 2), C(r - 2, r - 2)}
Fractals of C(n - 3, r - 1) - [from z = 1 to z = n - r -1] y {C(n - z - 3, r - 2)}
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Fractals of C(r + 1, r - 1) - {C(r, r - 2), C(r - 1, r - 2), C(r - 2, r - 2)}
Fractals of C(r + 1, r - 1) - [from z = 1 to z = 3] y {C(r - z + 1, r - 2)}
Fractals of C(r, r - 1) - {C(r - 1, r - 2), C(r - 2, r - 2)}
Fractals of C(r, r - 1) - [from z = 1 to z = 2] y {C(r - z, r - 2)}
Fractals of C(r - 1, r - 1) - {C(r - 2, r - 2)}
Fractals of C(r - 1, r - 1) - [from z = 1 to z = 1] y {C(r - z - 1, r - 2)}
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