Timeline for Establishing the Probability Distribution that Governs a Random Process
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| Jan 29, 2022 at 1:26 | history | edited | kjetil b halvorsen♦ | CC BY-SA 4.0 |
added 289 characters in body
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| Apr 11, 2018 at 20:42 | comment | added | MoonKnight | @A.G. Sorry I have just gotten around to going through this - this is an AWESOME answer! Thanks very much for your help. But I wondered if I could ask you a few questions - I am happy to open up another question with bounty if required. The first question is (I have checked the MASS package documentation) what are the size and mu parameters in relation to the negative binomial distribution which usually uses r and p? | |
| Apr 11, 2018 at 18:51 | vote | accept | MoonKnight | ||
| Feb 16, 2018 at 21:35 | history | bounty ended | CommunityBot | ||
| S Feb 13, 2018 at 18:20 | history | suggested | Jim | CC BY-SA 3.0 |
makes code runnable: prefix `count.` was missing, now added.
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| Feb 13, 2018 at 18:08 | review | Suggested edits | |||
| S Feb 13, 2018 at 18:20 | |||||
| Feb 13, 2018 at 15:47 | comment | added | A. G. | No problem. I'd love to know why someone downvoted too. My answer does not explicitly formulate a log-likelihood and solve it, but the question didn't ask for that: it simply wants an R script to do the estimation, which is what my answer provides, together with a full explanation. | |
| Feb 13, 2018 at 15:17 | history | answered | A. G. | CC BY-SA 3.0 |