Timeline for How can I calculate a joint distribution based on marginal and conditional information?
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| Dec 26, 2022 at 15:11 | history | undeleted | whuber♦ | ||
| Dec 26, 2022 at 15:11 | history | edited | whuber♦ | CC BY-SA 4.0 |
added 69 characters in body
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| Mar 9, 2022 at 17:00 | history | deleted | Cesar M♦ | via Vote | |
| Oct 5, 2020 at 4:26 | comment | added | John Walsh | Calculating the marginal PMF from the Joint PMF by using the tabular method. See nice table produced above in this string. We know that adding rows or columns to get the Marginal PMF. Rows PK (k) and Columns PN(n). I am not quite sure, but I believe Marginal PMF of PN(n) = Summation 1/2 * n * [2^(-k)] /2n Marginal PMF of PK (k) = Summation 1/2 * n * 2 * [2^(-2k+1)]/2n Feel free to find my errors or show that I have correctly interpreted the graphical output above. | |
| Mar 2, 2020 at 18:00 | history | tweeted | twitter.com/StackStats/status/1234539122741710848 | ||
| Mar 2, 2020 at 16:34 | vote | accept | Hugo | ||
| Mar 2, 2020 at 16:23 | answer | added | whuber♦ | timeline score: 4 | |
| Mar 2, 2020 at 15:31 | comment | added | whuber♦ | I find that visualizing the joint distribution with diagrams like the first one at stats.stackexchange.com/a/104018/919 can be helpful in working through problems like this. You can construct such a diagram from the conditional distribution: in effect, it tells you how to draw each column of dots on $(n,k)$ axes, and then finding the marginal distribution of $K$ is matter of adding up the rows of probabilities. | |
| Mar 2, 2020 at 8:26 | answer | added | gunes | timeline score: 2 | |
| Mar 2, 2020 at 2:39 | history | edited | Hugo | CC BY-SA 4.0 |
Added some of my own efforts to try to solve this question.
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| Mar 2, 2020 at 2:13 | history | asked | Hugo | CC BY-SA 4.0 |