Timeline for How to smooth data and force monotonicity
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| S Apr 1 at 13:52 | history | suggested | mcmuffin6o |
Add R tag to the list of tags
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| Apr 1 at 2:31 | review | Suggested edits | |||
| S Apr 1 at 13:52 | |||||
| Jan 31, 2019 at 15:48 | history | edited | kjetil b halvorsen♦ | CC BY-SA 4.0 |
deleted 18 characters in body
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| Jan 31, 2019 at 15:47 | comment | added | kjetil b halvorsen♦ | Similar Q with answer: stats.stackexchange.com/questions/206073/… | |
| Nov 28, 2017 at 15:36 | answer | added | srepho | timeline score: 22 | |
| Feb 21, 2016 at 2:58 | comment | added | Glen_b |
I notice your example values are integer. Are your real values counts? If they were, then (while this is no guarantee of monotonicity, for data like these it will generally give it anyway), something like this might be useful: plot(y~x,data=df); f=fitted( glm( y~ns(x,df=4), data=df,family=quasipoisson)); lines(df$x,f)
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| Feb 19, 2016 at 22:20 | vote | accept | Ben | ||
| Feb 19, 2016 at 20:26 | answer | added | Gavin Simpson | timeline score: 30 | |
| Feb 19, 2016 at 19:58 | history | asked | Ben | CC BY-SA 3.0 |