Timeline for Estimating distribution from censored data
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| Mar 26, 2015 at 14:10 | history | edited | whuber♦ | CC BY-SA 3.0 |
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| Dec 19, 2013 at 0:02 | history | edited | Andris Birkmanis | CC BY-SA 3.0 |
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| Dec 18, 2013 at 23:53 | history | edited | Andris Birkmanis | CC BY-SA 3.0 |
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| Dec 18, 2013 at 23:31 | history | edited | Andris Birkmanis | CC BY-SA 3.0 |
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| Dec 18, 2013 at 23:27 | comment | added | Andris Birkmanis | One problem with current code is it allocates fractional counts of hidden data, which may produce unrealistic parameters. I leave this fix as an exercise :) | |
| Dec 18, 2013 at 23:18 | comment | added | Andris Birkmanis | I followed the idea mentioned in Parameter Estimation from Censored Samples using the Expectation-Maximization Algorithm, Section 3. I estimate parameters (in my case, the discrete distribution itself) from observed data, then iteratively "sample" (actually allocate proportionally) hidden data according to current parameters, then re-estimate parameters given both observed and "guessed" hidden data, until parameters stop changing significantly. Now, I would be glad to find a method without iterations - not sure if it's possible. | |
| Dec 18, 2013 at 23:16 | comment | added | whuber♦ | An explanation of what this code is doing would be welcome. | |
| Dec 18, 2013 at 23:15 | history | edited | Andris Birkmanis | CC BY-SA 3.0 |
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| Dec 18, 2013 at 23:09 | history | edited | Andris Birkmanis | CC BY-SA 3.0 |
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| Dec 18, 2013 at 23:02 | history | answered | Andris Birkmanis | CC BY-SA 3.0 |