Timeline for How to predict values or estimate quantiles beyond the range of a sample?
Current License: CC BY-SA 3.0
8 events
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| Aug 24, 2017 at 15:59 | history | edited | Firebug |
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| Sep 26, 2016 at 14:49 | history | edited | whuber♦ | CC BY-SA 3.0 |
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| Sep 26, 2016 at 14:10 | answer | added | whuber♦ | timeline score: 2 | |
| Sep 26, 2014 at 22:30 | comment | added | ziggle314 | This is actually a tolerance issue. So I have 10 data samples that are well within the threshold. I am now asked what is the probability of exceeding the threshold value. Intuitively, it seems like I cannot estimate that number without a parametric model. I am just trying to see if I am missing something here. | |
| Sep 26, 2014 at 22:19 | comment | added | James | Do you need the probability that a newly observed point is beyond the already observed range, or you also need to know by how much? | |
| Sep 26, 2014 at 21:52 | comment | added | whuber♦ | The point made by @soakley might be even a little clearer if it is understood that it does not refer to the chance that the 11th point is the greatest one conditional on the data (the 10 points). That chance cannot be estimated, because these 10 points could be any subset of the population. But if you contemplate this event before data collection and ask for its chance, that can be estimated because all 11 values are random, independent, and identically distributed. Moreover, if you also assume a continuous distribution, the chance can be computed exactly. | |
| Sep 26, 2014 at 21:28 | comment | added | soakley | Say you have a sample of 10 data points. What is the chance that an 11th data point is greater than the 10 you have collected? | |
| Sep 26, 2014 at 21:24 | history | asked | ziggle314 | CC BY-SA 3.0 |