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27 views

Posterior covariance of Normal-Inverse-Wishart not converging properly

I am trying to implement a simple normal-inverse-Wishart conjugate prior distribution for a multivariate normal with unknown mean and covariance in numpy/scipy such that it can take a data vector and ...
24 views

Sample from Wishart distribution with inverse Scale matrix

I tried to model precision matrix in a hierarchical Bayesian setup with Wishart prior given d.f. and inverse scale matrix, and matrix normal likelihood, since it's a conjugate prior, my posterior on ...
46 views

Entropy of Inverse-Wishart distribution

What is entropy of Inverse-Wishart distribution? I need just a reference, but derivation (e.g. using inverse property) would be interesting too.
33 views

Matching X'X with Wishart Samples in R

$X'X \sim Wishart(\Sigma,n)$, however I'm having a tough time producing this in R. Example: ...
50 views

What is the distribution of the trace of an inverse Wishart distribution?

Given a Wishart distributed matrix $S$, what is the distribution of $\text{Tr}(S^{-1})$? What I can get to is Each diagonal element of $S$ is inverse gamma I can get the distribution of a sum of ...
127 views

How to specify the Wishart distribution scale matrix

I'm running the below Bayesian mixing model in R using the rjags package, but I am having difficultly in specifying the scale matrix for the Wishart distribution. Essentially, I want Sigma.inv to be a ...
39 views

How do you translate a density from Cholesky factor to density of the matrix?

Suppose $L$ is a random $p\times p$ lower triangular matrix, with known density, $f(L)$. To compute the density of $C=L L^{\top}$, one needs to use the change of density formula. This is a little bit ...
98 views

Generate covariance matrix with fixed values in certain cells

I want to be able to generate a covariance matrix of dimensions $D$ x $D$, such that certain specified cells of this matrix contain a fixed predetermined values (at least approximately). For e.g. For ...
94 views

Degrees of freedom for Gaussian Process

I am reading this paper on Generalised Wishart Process (GWP). It is about modelling covariance matrix of D - dimensional gaussian processes (GP) as GWP. I fail to understand interpretation of "degrees ...