Timeline for Error function of multivariate Gaussian
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 30, 2020 at 4:20 | comment | added | Rafael | I'll work on the definitions over this month and try to organize the problem more rigorously. Thanks again for the comments, it has helped me think about the details of this, which is going to be in my master thesis. | |
| Dec 30, 2020 at 1:40 | comment | added | Iosif Pinelis | That would make more sense. But then you would have to define the measure on $V$ over which you want to integrate. | |
| Dec 29, 2020 at 21:23 | comment | added | Rafael | I have just realized, that my problem is defined only in the orthogonal complement $V$ you defined, because I'm working with a convolution of this function. I will work on it. Thanks for the comments! | |
| Dec 29, 2020 at 16:40 | comment | added | Rafael | Well, I guess this solves what I was trying. I'm going to try something else here. The problem is restricted to positive integers as components of $\vec{y}$, but I was trying to extend it to $\mathbb{R}$. Thanks for the help! | |
| Dec 29, 2020 at 16:37 | vote | accept | Rafael | ||
| Dec 29, 2020 at 3:57 | comment | added | Iosif Pinelis | I did not have a problem with $k$ denoting the dimension and $k_n$ denoting the kernel. The problem is with the fact that $Q$ is a singular (positive-semidefinite) matrix, rather than a positive-definite one. | |
| Dec 29, 2020 at 0:40 | comment | added | Rafael | I'm editing the question again, but your clever decomposition of the matrix has already helped me a great deal! | |
| Dec 29, 2020 at 0:39 | comment | added | Rafael | After reading this comment I was really confused about what went wrong with my idea. I have just seen, that I forgot to mention an important detail: $k\in\mathbb{N}$ is also the size of the matrix, so that $Q$ is positive semi-definite. I'm terribly sorry for the misunderstanding. I have been working on the problem leading to this question for so long, that it didn't even occurred to me to mention. | |
| Dec 28, 2020 at 19:10 | comment | added | Iosif Pinelis | Clearly, no strictly positive normalizing factor can possibly help here. | |
| Dec 28, 2020 at 2:10 | comment | added | Rafael | Thank you for your answer! I have realized that the definition of $k_N$ is wrong. The function should be normalized. I'm going to edit the definition. | |
| Dec 28, 2020 at 0:02 | history | answered | Iosif Pinelis | CC BY-SA 4.0 |