ABSTRACT
Likelihood functions are a parameter estimation approach that assumes model-data residuals are characterized with probability distributions. The best parameters are then determined from optimization of the likelihood function. In this chapter we build an understanding of continuous probability distributions and then visualize likelihood functions with functions from the demodelr package.
