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# [Algebra common utilities](@id lib-helpers-algebra-common) | ||
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## [diageye](@id lib-helpers-algebra-diageye) | ||
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```@docs | ||
diageye | ||
ReactiveMP.CompanionMatrix | ||
ReactiveMP.PermutationMatrix | ||
ReactiveMP.StandardBasisVector | ||
ReactiveMP.GammaShapeLikelihood | ||
ReactiveMP.ImportanceSamplingApproximation | ||
ReactiveMP.mul_inplace! | ||
ReactiveMP.negate_inplace! | ||
ReactiveMP.mul_trace | ||
ReactiveMP.rank1update | ||
ReactiveMP.v_a_vT | ||
ReactiveMP.powerset | ||
ReactiveMP.besselmod | ||
``` |
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# [Marginal implementation](@id lib-marginal) | ||
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## Marginal type | ||
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All marginals are encoded with the type `Marginal`. | ||
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```@docs | ||
Marginal | ||
``` | ||
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From an implementation point a view the `Marginal` structure does nothing but hold some `data` object and redirects most of the statistical related functions to that `data` object. However, this object is used extensively in Julia's multiple dispatch. | ||
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```@docs | ||
ReactiveMP.getdata(marginal::Marginal) | ||
ReactiveMP.is_clamped(marginal::Marginal) | ||
ReactiveMP.is_initial(marginal::Marginal) | ||
ReactiveMP.getaddons(marginal::Marginal) | ||
ReactiveMP.as_marginal | ||
ReactiveMP.to_marginal | ||
``` | ||
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```@example marginal | ||
using ReactiveMP, BayesBase, ExponentialFamily | ||
distribution = ExponentialFamily.NormalMeanPrecision(0.0, 1.0) | ||
marginal = Marginal(distribution, false, true, nothing) | ||
``` | ||
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```@example marginal | ||
mean(marginal), precision(marginal) | ||
``` | ||
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```@example marginal | ||
logpdf(marginal, 1.0) | ||
``` | ||
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```@example marginal | ||
is_clamped(marginal), is_initial(marginal) | ||
``` |
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