@@ -14,15 +14,15 @@ choosing `probs` to be an array of one higher dimension than the array
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generated.
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Here the word "probabilities" is an abuse of terminology as there is
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- no requirement that the that probabilities actually sum to one. Indeed
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- there is no restriction on the probabilities at all. In particular,
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- `UnivariateFinite` objects implement arbitrary non-negative, signed,
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- or complex measures over finite sets of labelled points. A
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- `UnivariateDistribution` will be a bona fide probability measure when
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- constructed using the `augment=true` option (see below) or when `fit`
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- to data. And the probabilities of a `UnivariateFinite` object `d` must
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- be non-negative, with a non-zero sum, for `rand(d)` to be defined and
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- interpretable.
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+ no requirement that the that probabilities actually sum to one. The
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+ only requirement is that the probabilities have a common type `T` for
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+ which `zero(T)` is defined. In particular, `UnivariateFinite` objects
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+ implement arbitrary non-negative, signed, or complex measures over
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+ finite sets of labelled points. A `UnivariateDistribution` will be a
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+ bona fide probability measure when constructed using the
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+ `augment=true` option (see below) or when `fit` to data. And the
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+ probabilities of a `UnivariateFinite` object `d` must be non-negative,
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+ with a non-zero sum, for `rand(d)` to be defined and interpretable.
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Unless `pool` is specified, `support` should have type
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`AbstractVector{<:CategoricalValue}` and all elements are assumed to
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