Bioequivalence and Bioavailability Forum 04:23 CET

Main page Policy/Terms of Use Abbreviations Latest Posts

 Log in |  Register |  Search

just y=ax+b [General Sta­tis­tics]

posted by nobody - 2017-10-08 20:26  - Posting: # 17879
Views: 7,358

(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

Complete thread:

 Mix view
Bioequivalence and Bioavailability Forum |  Admin contact
18,939 posts in 4,040 threads, 1,288 registered users;
online 11 (0 registered, 11 guests [including 5 identified bots]).

Outside his own ever-narrowing field of specialization,
a scientist is a layman.
What members of an academy of science have in common
is a certain form of semiparasitic living.    Erwin Chargaff

BEBAC Ing. Helmut Schütz