maximum likelihood estimate

We talked about the MLE. Maybe it seems somewhat difficult for us to explain the real meaning of MLE, but there are several examples we used to let us know that made it easily undetstood.
Note that the maximum likelihood estimator may not be unique, or indeed may not even exist.

Maximum likelihood estimation (MLE) is a popular statistical method used for fitting a mathematical model to some data. Modeling real world data by estimating maximum likelihood offers a way of tuning the free parameters of the model to provide a good fit.

For examples, you are willing to assume that heights are normally distributed with some unknown mean and variance. The sample mean is then the maximum likelihood estimator of the population mean, and the sample variance is a close approximation to the maximum likelihood estimator of the population variance


http://raschsmile.blogspot.com/2006_08_01_archive.html

http://www.psy.vanderbilt.edu/faculty/palmeri/P351-modeling/readings/myung-tutorial-mle.pdf