Maximum Likelihood Estimator (MLE) is a statistical method for estimating the parameters of a probability distribution by maximizing the likelihood function based on the given sample data.
The Monte Carlo Method is a computational algorithm that relies on repeated random sampling to estimate the statistical properties of a system. It is widely used in fields ranging from finance to physics for making numerical estimations.
An in-depth look at the Tobit Model, a regression model designed to handle censored sample data by estimating unknown parameters. Explore its historical context, applications, mathematical formulation, examples, and more.
