Timeline for What are "prior distribution" and "posterior distribution" in the case of Bayesian statistics? [closed]
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
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| Apr 8, 2022 at 3:53 | history | closed |
Xi'an kjetil b halvorsen♦ |
Needs details or clarity | |
| Apr 6, 2022 at 10:29 | comment | added | Firebug | @Tim since it's about Bayesian statistics I thought it followed directly from that definition, and not for the general Bayes' Theorem, which is not exclusively Bayesian | |
| Apr 6, 2022 at 9:27 | vote | accept | user366312 | ||
| Apr 6, 2022 at 9:23 | comment | added | PaulG | By "distribution" do you mean densities (PDFs)? If yes, then the question of deriving Bayes' formula for densities from probabilities is indeed not trivial (see Papoulis 2002. Probabilities Random Variables and Stochastic Processes. Chp4-4). But if you mean CDFs then Bayes' theorem for CDFs follows immediately from Bayes' theorem for probabilities since CDFs are probabilities (i.e. needs only replacing the event with the random variable e.g. $P(A)$ with $P(X\le x)$). | |
| Apr 6, 2022 at 9:21 | review | Close votes | |||
| Apr 8, 2022 at 3:53 | |||||
| Apr 6, 2022 at 8:32 | answer | added | BruceET | timeline score: 0 | |
| Apr 6, 2022 at 8:26 | comment | added | Tim | @Firebug you can write down Bayes theorem for events so your comment may be unclear without further clarification. | |
| Apr 6, 2022 at 8:24 | answer | added | Tim | timeline score: 2 | |
| Apr 6, 2022 at 6:42 | comment | added | Firebug | I think you have it switched: when we say priors, we mean prior probability distributions. Priors are always defined as distributions. | |
| Apr 6, 2022 at 6:34 | history | asked | user366312 | CC BY-SA 4.0 |