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##### 負二項分佈表打印實例( Negative Binomial Table Printing Example).

```// 打印一個表的值，使得這些數值可以用於 Excel，或其它的圖像顯示工具繪製出圖像.

cout.precision(17); // 使用 max_digits10 精度， 對於一個參考表的可用的最大值.
cout << showpoint << endl; // 包含試驗0次.
// 這是對於適合這個參考表的類型(這裡是double類型)的最大可能精度.
int maxk = static_cast<int>(2. * mynbdist.successes() /  mynbdist.success_fraction());
//  maxk 顯示了大部分的我們關注的範圍，概率大約是0.0001 到 0.999.
cout << "\n"" k            pdf                      cdf""\n" << endl;
for (int k = 0; k < maxk; k++)
{
cout << right << setprecision(17) << showpoint
<< right << setw(3) << k  << ", "
<< left << setw(25) << pdf(mynbdist, static_cast<double>(k))
<< left << setw(25) << cdf(mynbdist, static_cast<double>(k))
<< endl;
}
cout << endl;
```

```k            pdf                      cdf
0, 1.5258789062500000e-005  1.5258789062500003e-005
1, 9.1552734375000000e-005  0.00010681152343750000
2, 0.00030899047851562522   0.00041580200195312500
3, 0.00077247619628906272   0.0011882781982421875
4, 0.0015932321548461918    0.0027815103530883789
5, 0.0028678178787231476    0.0056493282318115234
6, 0.0046602040529251142    0.010309532284736633
7, 0.0069903060793876605    0.017299838364124298
8, 0.0098301179241389001    0.027129956288263202
9, 0.013106823898851871     0.040236780187115073
10, 0.016711200471036140     0.056947980658151209
11, 0.020509200578089786     0.077457181236241013
12, 0.024354675686481652     0.10181185692272265
13, 0.028101548869017230     0.12991340579173993
14, 0.031614242477644432     0.16152764826938440
15, 0.034775666725408917     0.19630331499479325
16, 0.037492515688331451     0.23379583068312471
17, 0.039697957787645101     0.27349378847076977
18, 0.041352039362130305     0.31484582783290005
19, 0.042440250924291580     0.35728607875719176
20, 0.042970754060845245     0.40025683281803687
21, 0.042970754060845225     0.44322758687888220
22, 0.042482450037426581     0.48571003691630876
23, 0.041558918514873783     0.52726895543118257
24, 0.040260202311284021     0.56752915774246648
25, 0.038649794218832620     0.60617895196129912
26, 0.036791631035234917     0.64297058299653398
27, 0.034747651533277427     0.67771823452981139
28, 0.032575923312447595     0.71029415784225891
29, 0.030329307911589130     0.74062346575384819
30, 0.028054609818219924     0.76867807557206813
31, 0.025792141284492545     0.79447021685656061
32, 0.023575629142856460     0.81804584599941710
33, 0.021432390129869489     0.83947823612928651
34, 0.019383705779220189     0.85886194190850684
35, 0.017445335201298231     0.87630727710980494
36, 0.015628112784496322     0.89193538989430121
37, 0.013938587078064250     0.90587397697236549
38, 0.012379666154859701     0.91825364312722524
39, 0.010951243136991251     0.92920488626421649
40, 0.0096507830144735539    0.93885566927869002
41, 0.0084738582566109364    0.94732952753530097
42, 0.0074146259745345548    0.95474415350983555
43, 0.0064662435824429246    0.96121039709227851
44, 0.0056212231142827853    0.96683162020656122
45, 0.0048717266990450708    0.97170334690560634
46, 0.0042098073105878630    0.97591315421619418
47, 0.0036275999165703964    0.97954075413276465
48, 0.0031174686783026818    0.98265822281106729
49, 0.0026721160099737302    0.98533033882104104
50, 0.0022846591885275322    0.98761499800956853
51, 0.0019486798960970148    0.98956367790566557
52, 0.0016582516423517923    0.99122192954801736
53, 0.0014079495076571762    0.99262987905567457
54, 0.0011928461106539983    0.99382272516632852
55, 0.0010084971662802015    0.99483122233260868
56, 0.00085091948404891532   0.99568214181665760
57, 0.00071656377604119542   0.99639870559269883
58, 0.00060228420831048650   0.99700098980100937
59, 0.00050530624256557675   0.99750629604357488
60, 0.00042319397814867202   0.99792949002172360
61, 0.00035381791615708398   0.99828330793788067
62, 0.00029532382517950324   0.99857863176306016
63, 0.00024610318764958566   0.99882473495070978
```