# s.s.o

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 Feb8 comment How to compute the generalization error (test error) in a multivariate regression? possible duplicate you can check this stats.stackexchange.com/questions/32748/… Oct23 comment What is the difference between estimation and prediction? İf you apply it to past e.g.a minimum-variance Kalman filter and a minimum-variance smoother may be used to recover data of interest from noisy measurements. The afore-mentioned techniques rely on one-step-ahead predictors... so, still prediction one step ahead (the future) :) Oct23 comment What is the difference between estimation and prediction? read it complete: Prediction is simply saying something about the future. Predictions are usually focused on outcomes and not the pathway to those outcomes. Oct23 answered What is the difference between estimation and prediction? Oct1 awarded Teacher Sep13 answered I have a very fuzzy data set, what can I do to 'smooth' it? Jul22 comment Multiple linear regression in MATLAB the difference between 70 observations and 70 responses is the residuals. the squared sum of the residuals are the general model error. the matlab code is just sum(resid.*resid). but note that sum squared error is just one of the ways to calculate general model error. Jul22 comment Multiple linear regression in MATLAB You just use 70 of them and the 70 response values to calculate model error. The other 30 and the response of 30 is just for model validation errors. they are two different errors. Jul22 comment Multiple linear regression in MATLAB lets say you have 100 data points you use 70 of them for the modeling and 30 for validation. you use those 70 for calculation of model generalization error via model residuals. Jul21 comment Multiple linear regression in MATLAB how about sum(resid) or sum(resid.*resid) en.wikipedia.org/wiki/Residual_sum_of_squares Jul21 answered Multiple linear regression in MATLAB May8 answered Similarity measures between curves?