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Back to the forum  Query: 2017-10-21 03:06 CEST (UTC+2h)

just y=ax+b [General Sta­tis­tics]

posted by nobody - 2017-10-08 20:26  - Posting: # 17879
Views: 491

(edited by nobody on 2017-10-08 20:45)

» x1=c(1,2,3,4,5)
» y1=c(10.5, 11.4, 12.6, 13.3, 14.6)
» x2=c(1,2,3,4,5)
» y2=c(10.3, 11.4, NA, 13.5, 14.6)

13.3 vs. 13.5? By intention?


The RMSE is the square root of the variance of the residuals. It indicates the absolute fit of the model to the data–how close the observed data points are to the model’s predicted values. Whereas R-squared is a relative measure of fit, RMSE is an absolute measure of fit. As the square root of a variance, RMSE can be interpreted as the standard deviation of the unexplained variance, and has the useful property of being in the same units as the response variable. Lower values of RMSE indicate better fit. RMSE is a good measure of how accurately the model predicts the response, and is the most important criterion for fit if the main purpose of the model is prediction."

...educated guess, no idea if sensitive for number of calibrators :-D

..didn't read it, maybe you want to have a look:

Kindest regards, nobody

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