Timeline for Lognormal distributions with different mean, but same standard deviation
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 10, 2017 at 15:32 | history | edited | whuber♦ | CC BY-SA 3.0 |
edited body; edited title
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| Nov 10, 2017 at 15:30 | answer | added | whuber♦ | timeline score: 3 | |
| Nov 10, 2017 at 4:11 | comment | added | floatingnode | Is it possible to preserve variance of the lognormal, but allow the underlying normal distribution to have a different variance than the original underlying normal distribution? I mean since I know the target mean (new value) and the target variance (=old variance), I can calculate the mu and sigma "parameters" for the transformed data? Now my question is given the new mu and sigma parameters, how can I transform the old data? I see X = exp(mu+sigma*z) where z is the normal standard distribution...but how to relate to the old data? | |
| Nov 10, 2017 at 3:49 | comment | added | Michael R. Chernick | The mean and variance of the lognormal distribution are both functions of the mean and variance of the underlying normal distribution. So you can't change the mean without changing the variance also and consequently the standard deviation. | |
| Nov 10, 2017 at 3:25 | review | First posts | |||
| Nov 10, 2017 at 4:35 | |||||
| Nov 10, 2017 at 3:21 | history | asked | floatingnode | CC BY-SA 3.0 |