Timeline for How can I check whether two signals are jointly normally distributed?
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
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| Mar 12, 2012 at 19:02 | vote | accept | Rachel | ||
| Mar 12, 2012 at 17:38 | history | tweeted | twitter.com/#!/StackStats/status/179260085011353600 | ||
| Mar 12, 2012 at 15:39 | answer | added | DWin | timeline score: 2 | |
| Mar 12, 2012 at 13:08 | comment | added | Rachel | @DilipSarwate That would be (b). I want a way to check whether the joint distribution is in fact normal. | |
| Mar 12, 2012 at 13:00 | comment | added | Dilip Sarwate |
This is a simulation where you begin with signals that are not jointly normal by construction, and your statistical procedure seems to be showing that one can be reasonably confident that the signals are in fact jointly normal. So, should you be checking whether (a) the statistical method was applicable, or correctly applied, or correctly interpreted, or (b) your signal generation method is leading to signals that are in fact jointly normal even though a prima facie case cannot be made for joint normality (as would be the case if s1 = randn(size(x,2));; s2 = randn(size(x,2));??
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| Mar 12, 2012 at 12:12 | answer | added | MånsT | timeline score: 6 | |
| Mar 12, 2012 at 12:05 | history | edited | Rachel | CC BY-SA 3.0 |
Added detail and images.
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| Mar 12, 2012 at 11:36 | history | asked | Rachel | CC BY-SA 3.0 |