Timeline for Statistical testing: do count data come from the same distribution?
Current License: CC BY-SA 4.0
17 events
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| Feb 12, 2023 at 16:46 | answer | added | Jarle Tufto | timeline score: 4 | |
| Feb 12, 2023 at 16:38 | comment | added | whuber♦ | As you suppose, I am only trying to help you articulate an understandable, answerable question. I am not offended when that doesn't happen, but I do appreciate knowing when it would not be worth the time to continue. | |
| Feb 12, 2023 at 16:17 | comment | added | Roger V. | @whuber I am ready to modify the question or provide additional information, if someone is interested in answering it. E.g., I have tried to give you multiple clarifications in the comments above... but I am even not sure, whether you are trying to answer or simply going through the motions of a moderator managing the community. Please do jot take it as an offense, but we are all busy people, and so since posting the question I have learned more by googling than from the community | |
| Feb 12, 2023 at 15:22 | comment | added | whuber♦ | In my experience, almost all questions that are stated abstractly fail to capture the unique or important aspects of the application, risking answers that are useless or misleading. | |
| Feb 12, 2023 at 15:18 | comment | added | Roger V. | @whuber In my experience giving too many technical details in this SE guarantees that the question remains unanswered... One way to describe the situation would be as a zero-inflated distribution - but this suggests specific kind of answers. | |
| Feb 12, 2023 at 15:05 | comment | added | whuber♦ | In the abstract setting you describe, I cannot determine what you might mean by "all counts come from the distribution" or by "permanently zero." These phrases might make sense in a particular application, so consider disclosing that in your post. | |
| Feb 12, 2023 at 9:51 | history | edited | Roger V. | CC BY-SA 4.0 |
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| Feb 12, 2023 at 9:39 | comment | added | Roger V. | @COOLSerdash thank you for pointing this! Indeed, the approach that I have adopted for now is to test the variance of the process vs. its mean. | |
| Feb 12, 2023 at 9:37 | comment | added | Roger V. | @whuber the problem is not to test whether the distribution is Poissonian, but whether all counts come from the distribution or not. Zeros may be due to $\lambda$ being small... or because they are permanently zero. | |
| Feb 11, 2023 at 22:21 | comment | added | whuber♦ | It sounds like most Poisson tests would apply, but if you could be more specific about your alternate hypothesis one might be able to develop a more powerful test appropriate for it. | |
| Feb 11, 2023 at 18:46 | comment | added | COOLSerdash | Couldn't you do a test for overdispersion in a Poisson model (as described here, for example)? Maybe I'm misunderstanding your question. | |
| Feb 11, 2023 at 18:25 | comment | added | Roger V. | @whuber if they are generated by different processes, then my null hypothesis is incorrect. For simplicity, one can consider that non-zero counts are still generated from a Poisson distribution, but zeros are just zeros - nothing happens. | |
| Feb 11, 2023 at 16:45 | comment | added | whuber♦ | You appear to change the question at the very end. If the zero and non-zero counts are "generated by different distributions," then exactly what is you model for them? It's obviously not Poisson! | |
| Feb 11, 2023 at 14:35 | history | edited | kjetil b halvorsen♦ |
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| Feb 11, 2023 at 8:45 | history | edited | Roger V. | CC BY-SA 4.0 |
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| Feb 11, 2023 at 6:57 | history | edited | Roger V. | CC BY-SA 4.0 |
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| Feb 10, 2023 at 17:27 | history | asked | Roger V. | CC BY-SA 4.0 |