Description Usage Arguments Details Value Author(s) See Also Examples
Creates an object representing a Normal-Gamma distribution. If (x,y) has a Normal-Gamma distribution, then the marginal distribution of y is a Gamma distribution, and the conditional distribution of x given y is normal.
1 | normalgamma(mu, kappa, alpha, beta)
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mu |
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kappa |
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alpha |
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If (x,y) has a Normal-Gamma distribution with parameters μ, κ, α, and β, then the marginal distribution of y has a Gamma distribution with parameters α and β, and conditionally on y, x has a normal distribution with expectation μ and logged standard deviation κ - log(y)/2. The probability density is proportional to
f(x,y)=y^{α-0.5}\exp(-y(β + e^{-2κ}(x-μ)^2/2))
A Normal-Gamma probability distribution.
Petter Mostad <mostad@chalmers.se>
gamma
, normal
, expgamma
, normalexpgamma
,
mnormal
, mnormalgamma
, mnormalexpgamma
1 | plot(normalgamma(3,4,5,6))
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