is SEE = RMSE? MSE = SSE / n-k-1 RMSE = sqrt (MSE) SEE = sqrt (SSE / n-k-1) what say?
agreed. RSS/TSS = R or R^2
Yes.
So SEE = RMSE. Are we saying this?
Ok several websites I have found say, RMSE = sqrt ( SSE / n) whereas SEE is sqrt ( SSE / (n-k-1)) I forgot the equation but there is an example in CFAI book
I think SEE is the variability of the residuals over the fitted line - i.e. it’s a standard deviation measure, but measures in-sample variability. Lower the better. RMSE is mostly used for out-of-sample predictions to see if the model is good for predicting beyond the sample space considered. Lower the better. So - they are the same mathematically. (I think so…) Missing JDV.
Me too :*-(