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When reading on the wikipedia page of Calibration they said :

" A reverse process to regression, where instead of a future dependent variable being predicted from known explanatory variables, a known observation of the dependent variables is used to predict a corresponding explanatory variable "

Indeed, this confuses me ! For me I see calibration is a special case of regression, and not a reverse regression. So, can some one explain the stated in wikipedia, or in general what is the difference between regression and calibration?

kjetil b halvorsen
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Nizar
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    Providing that the correlation between $X$ and $Y$ is not $\pm1$, regressing $X$ on $Y$ will suggest a different relationship between them compared with regressing $Y$ on $X$. So trying to predict a value $\hat{x}$ from an observation $y ( \not = E[Y])$ will usually give different results depending on whether you use direct regression or reverse regression – Henry Aug 24 '17 at 06:40
  • @Henry Thank you for your commetn, but to clarify my question, I am asking about calibration and not reverse regression ! – Nizar Aug 24 '17 at 07:24
  • For additional discussions of this please see https://stats.stackexchange.com/questions/31528 and https://stats.stackexchange.com/questions/38023. – whuber Aug 24 '17 at 14:27

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