Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for statistical model fitting.The text presents algorith
Programming and R. Statistics and Likelihood-Based Estimation. Ordinary Regression. Generalized Linear Models. Maximum Likelihood Estimation. Panel Data. Model Estimation Using Simulation. Bibliography. Index.