# Questions tagged [gaussian]

For questions about the Gaussian probability distribution, its definition, properties and use.

50 questions
Filter by
Sorted by
Tagged with
4 views

### Gaussian width after some linear transformation

The Gaussian width $w(T)$ of a set $T\in \mathbb{R}^n$ is defined as follows: $$w(T) = \mathbb{E}\sup_{x\in T} \langle g,x\rangle$$ where $g$ is a random normal vector in $\mathbb{R}^n$. The ...
20 views

### Gaussian subdivision surfaces paper, typo?

I am reading a CG paper that came on 2019 and I am stuck at one section. After thinking about my issue I am starting to believe the author made a typo, but the likelihood of me being wrong is much ...
27 views

16 views

### Graphical models for regression problem

I am studying about the Gaussian graphical model (GGM). I have a $N\times D$ matrix X of my observations. The structure of the network has been found by using the graphical lasso method. It means I ...
24 views

### regarding the concept of infinite long vector and function

When learning the Gaussian process, there is a concept stating that " infinite long vector is similar to function", which is shown in the attached image. What does it mean, I am not very clear about ...
12 views

### Can properties for (circular symmetric) complex random matrices automatically work for real random matrices?

I am dealing with a theorem which relates to circularly symmetric complex Gaussian random matrices (CSGRM). It seems quite tempting to assume that the theorem also extends to real-valued Gaussian ...
22 views

16 views

13 views

34 views

### Two random variables not gaussian but whose sum is gaussian

It is well known that if $X$ and $Y$ are two independent gaussian random variables, or if $(X,Y)$ is jointly bivariate gaussian, then the sum $X+Y$ is a gaussian random variable. It is also known that ...
30 views

### Predictive distribution of SPGP

Eq(8) in Sparse Gaussian Processes using Pseudo-inputs states that \begin{align*} "p(y^*|x^*,D,\bar{X})=\int{p(y^*|x^*,\bar{X},\bar{f})p(\bar{f}|D,\bar{X})d\bar{f}}" \end{align*} which can be ...
20 views

26 views

### how was the gaussian distribution developed? (question of an answer already done)

I was looking for an answer for this question, I found it here on math stackexchage, but there's something in the answer I did not understand. I tried to add a comment too the answer, but I couldn't, ...
Assume that $X = (X_1, ... , X_n)$ are jointly Gaussian distributed. Can I then say that each of $X_1, ... , X_n$ is Gaussian distributed? Can I deduce that they are pairwise independent?