PDF¶
Status: Stable
documented, exercised by the test suite and/or worked examples, with no known limitations recorded.
Description¶
PDF[dist, x] gives the probability density of dist at x, and threads over a list of x. Supports NormalDistribution and UniformDistribution.
Examples (3)¶
Every input below was run against the current Mathilda build and its output recorded.
Basic examples (3)¶
In[1]:= SeedRandom[42]; RandomVariate[NormalDistribution[], 5]
Out[1]= {0.981398, -0.56572, 1.34033, 0.402313, -0.964221}
In[2]:= SeedRandom[1]; s = RandomVariate[NormalDistribution[5., 2.], 20000]; {Mean[s], StandardDeviation[s]}
Out[2]= {5.00479, 1.99627}
In[3]:= PDF[NormalDistribution[], {-1., 0., 1.}]
Out[3]= {0.241971, 0.398942, 0.241971}
Implementation notes¶
Attributes: Protected.
References¶
- Source:
src/ml/dist.c - Specification:
docs/spec/builtins/machine-learning.md - Tests:
tests/test_ml_classify.c - Tests:
tests/test_ml_dist.c