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