I am going through Casella's statistical inference in one-semester standard statistic course and have mathematical background from Sheldon Axler's linear algebra done right and Louis Brand's advanced calculus. I wish to self-study these topics:
- Lindeberg condition
- Analysis of variance
- Akaike Information Criterion
- Bayesian Information Criterion
- Eigenvalue decomposition
These are truly divergent topics, so I am wondering are there a single textbook dealing these topics and I can read it from cover to cover? I have much difficulty finding sources covering the last 3 topics, so a source covering the last 3 topics also suffices. My goal is to get full understanding of these topics so a textbook with detailed elaboration will be the best choice.