Jiming Jiang is Professor of Statistics and a former Director of Statistical Laboratory at the University of California, Davis. He is a prominent researcher in the fields of mixed effects models, small area estimation, model selection, and statistical genetics. He is the author of Linear and Generalized Linear Mixed Models and Their Applications, 2nd Edition (Springer 2021), Robust Mixed Model Analysis (2019), Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems (2017), and The Fence Methods (with T. Ngyuen, 2016). Jiming Jiang has been editorial board member of The Annals of Statistics and Journal of the American Statistical Association, among others. He is a Fellow of the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics; an elected member of the International Statistical Institute; and a Yangtze River Scholar (Chaired Professor, 2017-2020).

Chapter 1. The -d Arguments.- Chapter 2. Modes of Convergence.- Chapter 3. Big O, Small o, and the Unspecified c.- Chapter 4. Asymptotic Expansions.- Chapter 5. Inequalities.- Chapter 6. Sums of Independent Random Variables.- Chapter 7. Empirical Processes.- Chapter 8. Martingales.- Chapter 9. Time and Spatial Series.- Chapter 10. Stochastic Processes.- Chapter 11. Nonparametric Statistics.- Chapter 12. Mixed Effects Models.- Chapter 13. Small-Area Estimation.- Chapter 14. Jackknife and Bootstrap.- Chapter 15. Markov-Chain Monte Carlo.- Chapter 16. Random Matrix Theory.