Timeline for MAP versus Component-Wise Maximum Marginal
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Aug 4, 2019 at 1:25 | comment | added | tisPrimeTime | Correct. That has been edited. | |
| Aug 4, 2019 at 1:25 | history | edited | tisPrimeTime | CC BY-SA 4.0 |
edited body
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| Aug 3, 2019 at 20:08 | comment | added | jbowman | I assume you meant $\arg \max$, not $\arg \min$, in your second equation? | |
| Aug 3, 2019 at 16:13 | answer | added | tmrlvi | timeline score: 1 | |
| Aug 3, 2019 at 16:02 | comment | added | tisPrimeTime | The relationship is arbitrary. Hence why I would love to see some counter examples of why the MAP over the joint doesn't necessarily correspond to the individual maximums across each marginal. :) | |
| Aug 3, 2019 at 16:00 | comment | added | tmrlvi | I'm asking about the connections between the density of the multivariate distribution and each marginal, since the answer depends mainly on that. For example, What is the connection between $p(\boldsymbol{x})$ and $p(x_1)$? if $p(\boldsymbol{x}) =\prod_{i=1}^{n} p(x_{i})$, then the components of the MAP over all is in fact the MAP in each marginal. Otherwise, we can build a counter example. | |
| Aug 3, 2019 at 15:58 | comment | added | tisPrimeTime | $\mathbf{x}$ is a vector and its components are given by $x_1, ..., x_n$. Let me know if you need further information, since I may have abused notation here. $p(\mathbf{x})$ is shorthand for the joint distribution | |
| Aug 3, 2019 at 15:57 | comment | added | tmrlvi | What is the connection between $p(\boldsymbol{x})$ and $p(x_1)$? | |
| Aug 3, 2019 at 14:54 | history | asked | tisPrimeTime | CC BY-SA 4.0 |