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...ability of adjustment but on their capability of prediction by calculating the (log)likelihood between predicted and observed values for each type of model. I found the following formula for Bernouilli model : -2 log lik = -2 sum (y*log phat + (1-y)*log(1-phat) ), with "phat" is the probaility (between 0 and 1) and "y" is the observed values (0 or 1). 1) Is anybody can tell me if this formula is statistically true? 2) Can someone tell me what is the formula of the likelihood between observed and predicted values for a gaussian model ? Thanks -- Christophe LOOTS PhD stud...

...apability of prediction by calculating the > (log)likelihood between predicted and observed values for each type of > model. > > I found the following formula for Bernouilli model : > > -2 log lik = -2 sum (y*log phat + (1-y)*log(1-phat) ), with "phat" is > the probaility (between 0 and 1) and "y" is the observed values (0 or 1). > > 1) Is anybody can tell me if this formula is statistically true? This looks correct. > 2) Can someone tell me what is the formula of the likelihood between > observed and predicted values for a gaussian...

Is anyone else concerned about the fact that rsync doesn't guarantee to produce identical file copies on the the target machine? Don't get me wrong in sounding critical because I think that rsync is a great example of how software should be written. (I often make the observation, as I learn more about Linux, and inevitably find myself comparing open source applications to Microsoft