Timeline for Copulas simply explained
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 4, 2016 at 6:08 | comment | added | Richi Wa | That's a basic property of a bivariate cdf.... It should be mentioned in introductory text books... | |
| Jul 3, 2016 at 19:04 | comment | added | Neeraj | Great, You can add this in your answer too. | |
| Jul 3, 2016 at 9:02 | comment | added | Richi Wa | @Neeraj $F_{X,Y}(x,y) = P[X \le x, Y \le y]$. Thus $F_{X,Y}(x,\infty) = P[X \le x, Y \le \infty]$. Obiously the set of events $\{Y \le \infty\}$ is trivial thus $P[X \le x, Y \le \infty] = P[X \le x] = F_X(x)$. | |
| Jul 1, 2016 at 16:30 | comment | added | Neeraj | It is bit confusing | |
| Jul 1, 2016 at 16:30 | comment | added | Neeraj | can you please explain the rationale for $F_{X,Y}(x,\infty) = F_{X}(x)$ | |
| Feb 24, 2015 at 16:43 | history | answered | Richi Wa | CC BY-SA 3.0 |