Gaussian latent tree models
DOI link for Gaussian latent tree models
Gaussian latent tree models book
Gaussian tree models. It turns out that this model has all the basic features of other models introduced earlier.
8.1 Gaussian models
Denote by PDm the set of symmetricm×mmatrices that are positive definite. We say that a random vector Y with values y in Rm has multivariate Gaussian distribution with the mean parameter µ ∈ Rm and the covariance matrix Σ ∈ PDm, which we denote by Y ∼ N(µ,Σ), if it has density with respect to the Lebesgue measure on Rm of the form:
fµ,Σ(y) = 1
(2pi)m/2 (det Σ)−1/2 exp(−1
2 (y − µ)TΣ−1(y − µ)).