Timeline for Testing for the existence of dependencies in time series
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
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| Mar 19, 2012 at 5:38 | history | tweeted | twitter.com/#!/StackStats/status/181615714258534400 | ||
| Nov 17, 2011 at 16:51 | history | edited | Pete | CC BY-SA 3.0 |
added another ref
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| Nov 17, 2011 at 16:43 | history | edited | Pete | CC BY-SA 3.0 |
update based on comments
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| Nov 17, 2011 at 16:29 | comment | added | Pete | @DmitrijCelov Yes, failing a (strong) test for independence would fit the bill. Can you suggest anything? Is Welch's Method applicable? | |
| Nov 17, 2011 at 14:59 | comment | added | Dmitrij Celov | So why are you actually not looking for the test on independence, with the alternative that some kind of dependence exists? Any (weak just zero mean, constant variance, uncorrelated OR strong + identically distributed) white noise tests are welcome here. | |
| Nov 17, 2011 at 5:06 | comment | added | Pete | @whuber Ideally, the test would conclude that the time series is not independent. In other words, a completely general test that could tell us when some sort of dependency exists, but not necessarily the kind of dependence. | |
| Nov 16, 2011 at 20:33 | comment | added | whuber♦ | What kind of "dependence" are you looking for specifically? After all, we could take a series $(x_1,\ldots,x_n)$ that satisfies your "differential spectrum test" and set $x_{n+j}=x_j+x_n-x_1$, $j=1,\ldots,n$. This series of $2n$ values would satisfy the test--the histogram is almost the same, with a slightly higher peak at $0$--but contains a very strong dependence indeed (half the values are completely determined by the other half)! Note, too, that your test is not a test of independence: it is merely a test of symmetry of first differences, which is much weaker than independence. | |
| Nov 16, 2011 at 20:25 | history | asked | Pete | CC BY-SA 3.0 |