Timeline for Detecting statistically significant clustering of continuous values
Current License: CC BY-SA 3.0
19 events
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| Apr 12, 2021 at 2:57 | history | edited | kjetil b halvorsen♦ |
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| Apr 18, 2014 at 22:15 | comment | added | Nick Cox | That seems singularly useless as a comment, either to me personally or to anyone else, unless you explain what's wrong and what's right. | |
| Apr 18, 2014 at 19:29 | comment | added | Greg Slodkowicz | @NickCox Having thought and researched this some more, you're misunderstanding the problem. | |
| S Sep 4, 2013 at 11:16 | history | bounty ended | CommunityBot | ||
| S Sep 4, 2013 at 11:16 | history | notice removed | CommunityBot | ||
| Aug 28, 2013 at 17:45 | comment | added | Greg Slodkowicz | I'm not being intentionally negative. I was just trying to avoid the question being marked as resolved when I believe that methods you're referencing don't apply -- at least not directly. | |
| Aug 28, 2013 at 17:36 | comment | added | Nick Cox | I don't know where the negativity comes from here. The initial comment was just a suggestion to "compare". The example in my posting was necessarily geared towards the question it answered, but my posting explained at length that there were other applications and there are references for further reading. Sorry, but we all ration our time, and I don't at present have time to rewrite an answer to another question to spell out its implications for yours. | |
| Aug 28, 2013 at 17:28 | comment | added | Greg Slodkowicz | Perhaps the references are relevant, the examples given in the thread are not, as far as I can tell. | |
| Aug 28, 2013 at 17:22 | comment | added | Nick Cox | Detecting runs of similar values is largely what the technique is all about. The references given are all very clear. | |
| Aug 28, 2013 at 17:20 | history | edited | Greg Slodkowicz | CC BY-SA 3.0 |
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| Aug 28, 2013 at 17:17 | comment | added | Greg Slodkowicz | Perhaps I'm missing the connection here. I didn't say that it matters where they come from, just that I believe the structure of my data is different. The income data in the example you linked can be reordered (hence my 'bag' metaphor) after which the presence of 'subdivisions' is assessed. My sampling points are constant (one continuous value for each integer in some range) and it doesn't make sense to reorder them. One way to phrase my problem would be that I'm interested in detecting presence of runs of similar values. | |
| Aug 28, 2013 at 16:25 | comment | added | Nick Cox | Absolutely not so. The posting and the references spell out that time, space and other sequences are all grist for the mill. Fisher's original example was a time series. Also, where the sequence comes from is immaterial to how you cluster it. What is excluded is clustering on two dimensions, for which you will certainly need quite different methods. | |
| Aug 28, 2013 at 13:26 | comment | added | Greg Slodkowicz | Thanks, but (as I see it) the thread you linked to is about addressing a slightly different question. My datapoints are in sequence whereas in the other case it's just as a 'bag' of unordered values that are then clustered. | |
| Aug 27, 2013 at 12:06 | history | tweeted | twitter.com/#!/StackStats/status/372329343558889472 | ||
| S Aug 27, 2013 at 9:38 | history | bounty started | Greg Slodkowicz | ||
| S Aug 27, 2013 at 9:38 | history | notice added | Greg Slodkowicz | Draw attention | |
| Aug 22, 2013 at 13:17 | history | edited | Nick Cox | CC BY-SA 3.0 |
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| Aug 22, 2013 at 13:17 | comment | added | Nick Cox | Compare stats.stackexchange.com/questions/67571/… | |
| Aug 22, 2013 at 13:11 | history | asked | Greg Slodkowicz | CC BY-SA 3.0 |