Methods of Statistical Model Estimation

Programming and R
Introduction
R Specifics
Programming
Making R Packages
Further Reading

Statistics and Likelihood-Based Estimation
Introduction
Statistical Models
Maximum Likelihood Estimation
Interval Estimates
Simulation for Fun and Profit

Ordinary Regression
Introduction
Least-Squares Regression
Maximum-Likelihood Regression
Infrastructure
Conclusion

Generalized Linear Models
Introduction
GLM: Families and Terms
The Exponential Family
The IRLS Fitting Algorithm
Bernoulli or Binary Logistic Regression
Grouped Binomial Models
Constructing a GLM Function
GLM Negative Binomial Model
Offsets
Dispersion, Over and Under
Goodness-of-Fit and Residual Analysis
Weights
Conclusion

Maximum Likelihood Estimation
Introduction
MLE for GLM
Two-Parameter MLE

Panel Data
What Is a Panel Model?
Fixed-Effects Model
Random-Intercept Model
Handling More Advanced Models
The EM Algorithm
Further Reading

Model Estimation Using Simulation
Simulation: Why and When?
Synthetic Statistical Models
Bayesian Parameter Estimation
Discussion

Bibliography

Index