Timeline for How to sample from truncated distributions using scipy?
Current License: CC BY-SA 4.0
17 events
| when toggle format | what | by | license | comment | |
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| Jul 13, 2021 at 5:34 | answer | added | famulare | timeline score: 1 | |
| Jul 13, 2021 at 4:04 | history | edited | Sycorax♦ | CC BY-SA 4.0 |
edited title
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| Jul 13, 2021 at 3:03 | answer | added | Sycorax♦ | timeline score: 7 | |
| Jul 12, 2021 at 23:33 | history | edited | Sycorax♦ | CC BY-SA 4.0 |
edited title
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| Jul 12, 2021 at 23:25 | history | reopened | Sycorax♦ | ||
| Jul 12, 2021 at 23:20 | comment | added | kms | Done. I edited question. | |
| Jul 12, 2021 at 23:19 | history | edited | kms | CC BY-SA 4.0 |
added 208 characters in body
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| Jul 12, 2021 at 23:17 | comment | added | Sycorax♦ | Can you edit your post to clarify that you are asking how to sample from truncated distributions? Right now, it's hard to understand what you want to know & where you are stuck | |
| Jul 12, 2021 at 23:06 | review | Reopen votes | |||
| Jul 12, 2021 at 23:26 | |||||
| Jul 12, 2021 at 23:03 | comment | added | kms | Yeah, I guess truncated distribution. | |
| Jul 12, 2021 at 23:01 | comment | added | kms | Ok. Say, growth variable can take values anywhere from -2 to 4% but with a non uniform distribution like gamma right, small chance it is <0. So then, how do I add a distribution around that constrain and sample from it? | |
| Jul 12, 2021 at 22:58 | comment | added | Sycorax♦ |
Are you asking how to sample from a distribution which has probability density proportional to disttype for values in [1,6] and probability 0 otherwise? In other words, how to sample from a truncated gamma, truncated log-normal, etc. distributions?
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| Jul 12, 2021 at 22:52 | comment | added | kms | Log-normal was an example I used. I need to constrain my data within an interval (1,6) and sample from this range by following a certain distribution type. @Sycorax | |
| Jul 12, 2021 at 22:49 | history | edited | kms | CC BY-SA 4.0 |
Added more info for clarity
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| Jul 12, 2021 at 22:39 | history | closed | Sycorax♦ | Needs details or clarity | |
| Jul 12, 2021 at 22:39 | comment | added | Sycorax♦ | The log-normal distribution doesn't have an upper limit, so either you don't want to draw from a log-normal distribution or you don't want to constrain the values to be in a certain range. Can you explain in more detail what problem you're trying to solve by drawing random samples in this way, and how a log-normal distribution fits with that goal? | |
| Jul 12, 2021 at 22:33 | history | asked | kms | CC BY-SA 4.0 |