search for: yhat_i

Does anyone know of a literature reference, or a piece of code that can help me calculate the amount of variation explained (R2 value), in a regression constrained to have a slope of 1 and an intercept of 0? Thanks! Sebastian J. Sebastián Tello Department of Biological Sciences 285 Life Sciences Building Louisiana State University Baton Rouge, LA, 70803 (225) 578-4284 (office and lab.)

...ms that the only alternative is to write the likelihood down and use optim or a similar function to get the MLE of the parameters of the model. I was also trying to compute Small Area Estimators using area level models, so that I have one observation per area. I tried to fit the following model: Yhat_i = X beta + u_i + e_i where Yhat is a direct estimator of the target variable, X, the area- level covariates, u_i the random effects independent and distributed as N(0, sigma2_u) and e_i the 'error' terms, which are distributed as N(0, sigma2_e/n_i), where n_i is the sample size in area i....

Hi, everybody, 3 questions about R-square: ---------(1)----------- Does R2 always increase as variables are added? ---------(2)----------- Does R2 always greater than 1? ---------(3)----------- How is R2 in summary(lm(y~x-1))$r.squared calculated? It is different from (r.square=sum((y.hat-mean (y))^2)/sum((y-mean(y))^2)) I will illustrate these problems by the following codes: