Thread: Stat Equations
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dipstik
07.30.2019 , 11:38 AM | #8
it is true that setting b=.01*a or setting b~=f(b,c) communicates the redundancy of variables. By setting c=1 i was able to get b=0.44849 to match my values. Using the values you mention (b~=45) dont seem to give matching values to my data set. I do like the elegance of b~=45, and looks close to my c=1.50344 solution.

Perhaps it would be helpful if we all post the points we are working with to resolve these regressions.

alacrity:
1725 9.63
1617 9.13
1509 8.62

crit:
1833
1725
1617

12.71
12.14
11.55

accuracy:
1832 10.11
1401 8.09
970 5.87

crit from mastery:
10614 11.55
9548 10.78
8690 10.12


defense:
285 1.76
570 3.42
855 4.99

shield:
431 4.34
840 8.11
1249 11.56

absorb:
409 4.91
818 9.34
1541 16.13

dmg red:

4782 15.06
4200 13.47
3212 10.64

health points:
15556 217785
14371 201188
13185 184590


theoretically we should be able to solve this with two data points for two unknowns (a and c assuming b=0.01*a, or a and b~).

Setting b=0.01*a (using old a values) I get for c values:

crit: 1.50344 a=30
alacrity: 2.0136 a=30
accuracy: 2.0181 a=30
def: 2.125 (Foyle) a=30
shield: 1.2789 (Foyle) a=50
absorb: 1.0656 a=50
crit from mastery: 8.4254 a=20
max health = 14*Endurance + 52295 (there is a - 7.72 offset that might not be real)
damage reduction = Armor_Rating/ (Armor_Rating+ 457.2399* 75 -7312.62 ) * 100