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travis-ci

stat/distuv: improve Gamma.Rand performances for 0.2 <= alpha < 1

The paper cited in the comment for the a > 1 (now a >= smallAlphaThresh) case mentions this approach as a small note on the final page, so there is no need to update the comments.

I also looked into numpy's logic for this case, but a) couldn't determine a source for it, except for what appears to be a more complex variant (Algorithm GS), and b) it's slightly slower than this method, at least for a >= 0.2.

benchstat:

```
name              old time/op  new time/op  delta
GammaRand/case_0  89.4ns ± 5%  90.2ns ± 3%     ~     (p=0.084 n=20+20)
GammaRand/case_1   212ns ± 3%   101ns ± 5%  -52.28%  (p=0.000 n=20+20)
GammaRand/case_2  25.4ns ± 3%  25.3ns ± 4%     ~     (p=0.369 n=20+20)
GammaRand/case_3  48.6ns ± 6%  48.8ns ± 6%     ~     (p=0.702 n=20+20)
GammaRand/case_4  47.1ns ± 6%  47.6ns ± 3%     ~     (p=0.147 n=20+20)
```

8 of 8 new or added lines in 1 file covered. (100.0%)

57408 of 74344 relevant lines covered (77.22%)

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