Timeline for Robust mean estimation with O(1) update efficiency
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
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| Jun 10, 2016 at 14:37 | vote | accept | Bitwise | ||
| Jun 10, 2016 at 14:37 | |||||
| Apr 24, 2014 at 15:07 | comment | added | whuber♦ | @Death As explained in the text immediately preceding the figure, the gray data are the original stream of data. Its running mean is the black curve. The colored curves are based on the algorithm. Vertical deviations of the colored curves relative to the black curve are due to the randomness in the sampling. The expected amount of deviation at any index is proportional to the standard deviation of the gray values preceding that index and inversely proportional to the square root of the sample size (taken as 50 in this example). | |
| Apr 23, 2014 at 20:42 | comment | added | Deathkill14 | Something is not clear to me in this example. Are the grey data "good" or "outliers." If the prior, it seems the fit is biased down (it should fit them better since the situation would be similar to @Bitwise's downward trend we would like to follow). If the grey data at higher index values is outliers, then it seems the fit is biased upwards. What is the target you want to fit here? The current fit seems torn between those two scenarios. | |
| Apr 23, 2014 at 13:56 | comment | added | whuber♦ |
@user603 The "rejection threshold," or whatever robust method is used to estimate the mean, is irrelevant: choose whatever method you wish to estimate the mean. (Not all robust methods work by erecting thresholds and rejecting data, BTW.) This would be done in the code of my answer by replacing summary by a robust variant.
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| Apr 23, 2014 at 6:46 | comment | added | user603 | it's not clear to me how the rejection threshold look like in this approach (e.g. the threshold beyond which observations are rejected as outliers). Can you add them to the plot? | |
| Apr 22, 2014 at 20:08 | history | edited | whuber♦ | CC BY-SA 3.0 |
added 21 characters in body
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| Apr 22, 2014 at 19:57 | history | answered | whuber♦ | CC BY-SA 3.0 |