0
votes
0answers
25 views

Two matrix Fisher distributions on SO(3)?

There seem to be two popular definitions of the matrix Fisher probability distribution on the Lie group SO(3): SO(3) is essentially the 3x2 matrices X such that XTX = I2, since the last column is ...
1
vote
0answers
18 views

the 3th and 4th order statistics of Circularly Symmetric Complex Normal random vector?

Assume that ${\bf{z}} \in {\mathbb{C}}^{n \times 1}$ is a CSCG random vector denoted with $\mathcal{C} ~ (\bf{\mu} _0,\bf \Sigma _0)$ where $\mu _0$ and $\bf \Sigma _0$ are mean and contrivance ...
0
votes
0answers
45 views

Distinguishing two different matrix distributions in polynomial time

I have two distributions: $\{ (f^TA + e_1, f^T(As+e) \}$ and $\{ (f^TA, f^T(As+e) + s_i \}$ where $A$ is a randomly generated $m \times n$ binary matrix $A, A_{ij} \in \{0,1\}$, $f$ and $e$ are a ...
1
vote
1answer
74 views

Numerical optimisation for multivariate Gaussians

Hi, I want to calculate $ f_{\mathbf x}(x_1,\ldots,x_k)\, = \frac{1}{(2\pi)^{k/2}|\boldsymbol\Sigma|^{1/2}} \exp\left(-\frac{1}{2}({\mathbf x}-{\boldsymbol\mu})^T{\boldsymbol\Sigma}^{-1}({\mathbf ...
4
votes
1answer
858 views

Monotonicity of the hard EM algorithm.

Consider the problem where we want to find a maximum likelihood estimate of $\theta$, given $X$ and $$P_\theta(Y) = \sum_z P_\theta(Y,x)$$ where $x$ is a latent variable. I know that the soft EM ...
1
vote
0answers
233 views

Eigenvectors of convolution with a normal distribution over a restricted interval

Suppose I have a random variable $X_0$ with a p.d.f $f_0$ supported on the real interval $[a_0, b_0]$. $X_1$ is the restriction to $[a_1, b_1]$ of the sum $X_0 + g$, where $g$ is normally distributed ...
2
votes
0answers
266 views

Seeking the normalizing constant (or any references) for a distribution over a subset of positive definite martrices

I'm interested in a probability distribution over the set of positive definite matrices with unit diagonal elements. That is, and $X$ such that: $X \in S^{n+}, \forall_{i}X_{ii} = 1$ where $S^{n+}$ ...