Parameter estimation typically involves statistical methods and mathematical modeling. Here are some common techniques: - Maximum Likelihood Estimation (MLE): A method that finds the parameter values that maximize the likelihood of observing the given data. - Bayesian Inference: Uses prior distributions and observed data to update the probability distributions of parameters. - Least Squares Estimation: Minimizes the sum of the squared differences between observed and predicted values. - Markov Chain Monte Carlo (MCMC) Simulation: A computational technique to sample from the posterior distribution of parameters.
