rcurtin commented on this pull request.
> + for(size_t i = 0; i < N; i++)
+ probabilities(i) = prob(generator);
+
+ // fit results with probabilities and data
+ GammaDistribution gDist;
+ gDist.Train(rdata, probabilities);
+
+ // fit results with only data
+ GammaDistribution gDist2;
+ gDist2.Train(rdata);
+
+ BOOST_REQUIRE_CLOSE(gDist2.Alpha(0), gDist.Alpha(0), 10);
+ BOOST_REQUIRE_CLOSE(gDist2.Beta(0), gDist.Beta(0), 10);
+
+ BOOST_REQUIRE_CLOSE(alphaReal, gDist.Alpha(0), 10);
+ BOOST_REQUIRE_CLOSE(betaReal, gDist.Beta(0), 10);
We can use a larger tolerance between the values of `alphaReal` and `betaReal`
and the estimated values, due to the noisy sampling from the gamma
distribution. I still think 10% tolerance is a bit large. But `gDist` and
`gDist2` should have virtually identical values so the tolerance should be very
small and 1e-5 should be fine. If that is causing the tests to fail, then I
think the implementation is incorrect.
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