On Sun, 2009-11-08 at 11:12 -0800, mat7770 wrote: > I have two related variables, each with 16 points (x and Y). I am given > variance and the y-intercept. I know how to create a regression line and > find the residuals, but here is my problem. I have to make a loop that uses > the seq() function, so that it changes the slope value of the y=mx + B > equation ranging from 0-5 in increments of 0.01. The loop also needs to > calculate the negative log likelihood at each slope value and determine the > lowest one. I know that R can compute the best regression line by using > lm(y~x), but I need to see if that value matches the loop functions.
Hi If I understand your question you need extract log-likelihood for a linear model, so you need using logLik command, see example: set.seed(1) x<-rpois(16,6) y<-2*x+3+rnorm(16,sd=3) model<-lm(y~x) logLik(model) 'log Lik.' -40.1177 (df=3) -- Bernardo Rangel Tura, M.D,MPH,Ph.D National Institute of Cardiology Brazil ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.