I don't know if I will explain this very well.
I try to test my methods by trying them on a problem with an obvious answer. Use insurance count (tag non-tens as -1 and tens as +2) (sign of tag relative to what remains in shoe) as the basis for a question.
For this count this is data listing min RC values for single deck where Prob(ten) >= 1/3, which we should agree on.
Code:
Count tags {-1,-1,-1,-1,-1,-1,-1,-1,-1,2}
Decks: 1
Insurance Data (without regard to hand comp)
No subgroup (removals) are defined
**** Player hand: x-x ****
Cards RC TC ref
48 0 0.00
47 1 1.11
46 2 2.26
45 0 0.00
44 1 1.18
43 2 2.42
42 0 0.00
41 1 1.27
40 2 2.60
39 0 0.00
38 1 1.37
37 2 2.81
36 0 0.00
35 1 1.49
34 2 3.06
33 0 0.00
32 1 1.63
31 2 3.35
30 0 0.00
29 1 1.79
28 2 3.71
27 0 0.00
26 1 2.00
25 2 4.16
24 0 0.00
23 1 2.26
22 2 4.73
21 0 0.00
20 1 2.60
19 2 5.47
18 0 0.00
17 1 3.06
16 2 6.50
15 0 0.00
14 1 3.71
13 2 8.00
12 0 0.00
11 1 4.73
10 2 10.40
9 0 0.00
8 1 6.50
7 2 14.86
6 0 0.00
5 1 10.40
4 2 26.00
3 0 0.00
2 1 26.00
1 2 104.00
Using TC as the index metric, obvious answer is buy insurance when TC > 0. Also acceptable, buy insurance when TC >= 0
For any of the above data points I can get this answer by interpolating to find RC when prob(ten) = 1/3, using 27, 26, 25 cards remaining as example.
27 cards (no interpolation necessary since prob(ten) = 1/3
RC = 0, prob(ten) = 1/3
TC = 52*0/27 = 0
26 cards single deck insurance (insurance count)
RC = +1, prob(ten) = 9/26
RC = -2, prob(ten) = 8/26
interpolate: RC = 0, prob(ten) = (8 2/3)/26
TC = 52*0/26 = 0
25 cards single deck insurance (insurance count)
RC = +2, prob(ten) = 9/25
RC = -1, prob(ten) = 8/25
interpolate: RC = 0, prob(ten) = (8 1/3)/25
TC = 52*0/25 = 0
This is my question:
How would your method of finding TC index work on this data set?
Thanks,
k_c
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