Timeline for How to estimate the probability mass function of a discrete variable from moments
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| Sep 17, 2022 at 18:55 | answer | added | kolbe | timeline score: 1 | |
| Mar 29, 2019 at 5:41 | answer | added | Ben | timeline score: 1 | |
| Mar 28, 2019 at 18:04 | comment | added | whuber♦ | Again, no penalty is needed: this is purely a linear program. Specifically, it's the first step of a linear program: find the set of feasible solutions. Your question doesn't describe any optimization problem at all. | |
| Mar 28, 2019 at 16:57 | comment | added | lordcretin | My question is how to set up the constrained linear problem. For example, should one use the objective function $||Ap-m||+pen(\sum p_i - 1)$ where the second term penalizes for solutions that are not valid PMFs? How would this approach compare to using the negative entropy objective function?A follow-up question is, how does this optimization approach compare with finding the PMF from the moment generating function? | |
| Mar 27, 2019 at 22:25 | comment | added | whuber♦ | Usually one solves this by minimizing some objective function, such as the negative entropy, subject to the constraints. But what are you asking? How to solve constrained linear problems? The question as you pose it is a linear program, so it's strange to see you ask whether "linear programming type ideas" would be applicable! | |
| Mar 27, 2019 at 21:51 | history | edited | lordcretin | CC BY-SA 4.0 |
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| Mar 27, 2019 at 21:28 | history | edited | lordcretin |
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| Mar 27, 2019 at 21:15 | history | asked | lordcretin | CC BY-SA 4.0 |