The extended maximum likelihood method allows for varying the normalization of probability distribution functions, making it useful when the number of samples is important. If the function can be adjusted in size and shape independently, the estimates are the same as standard maximum likelihood. However, if the function cannot be adjusted in this way, extended maximum likelihood can provide more accurate results.