Description Usage Arguments Details Value Author(s) See Also Examples
Creates an object representing a multivariate Normal-ExpGamma distribution. If (x,y) has a multivariate Normal-ExpGamma distribution, then the marginal distribution of y is an ExpGamma distribution, and the conditional distribution of x given y is multivariate normal.
1 | mnormalexpgamma(mu=c(0,0), P, alpha, beta)
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mu |
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If (x,y) has a multivariate Normal-ExpGamma distribution with parameters μ, P, 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 multivariate normal distribution with expectation μ and precision matrix e^{-2y}P. The probability density is proportional to
f(x,y)=\exp(-(2α + k)y - e^{-2y}(β + (x-μ)^tP(x-μ)/2))
where k is the dimension.
A multivariate Normal-ExpGamma probability distribution.
Petter Mostad <mostad@chalmers.se>
gamma
,normal
,expgamma
,
normalgamma
,normalexpgamma
mnormal
,mnormalgamma
1 | plot(mnormalexpgamma(alpha=3, beta=3))
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