Best suggested textbooks on Bootstrap resampling? I just wanted to ask which are in your opinion the best available books on bootstrap out there. By this I don't necessarily only mean the one written by its developers.
Could you please indicate which textbook is according to you the best for bootstrap that covers the following criteria?


*

*The philosophical/epistemological basis for the technique that
lists domain of applicability, strengths and weaknesses, importance
for model-selection?

*A good set of simple examples that show implementation,
philosophical underpinnings, preferably with Matlab?

 A: It might be worth going back to the origins of Bootstrapping and learning a bit about jackknifing from sources such as Quenouille and Tukey. Personally, the book "Data analysis and regression : a second course in statistics" by Mosteller and Tukey really helped me when I was first learning about bootstrapping.
A: There are two "classic" ones:
Efron, B. & Tibshirani, R. J. (1993). An introduction to the bootstrap. London: Chapman & Hall/CRC.
Davison, A. C. & Hinkley, D. V. (2009). Bootstrap methods and their application. New York, NY: Cambridge University Press.
The first one is very readable and gives you good idea what bootstrap is and what is the general reasoning behind this method. It also provides many examples and practical hints about using bootstrap in real life. The second is a really extensive review of different usages of bootstrap, with lots of examples and also examples of code written in R. I would say that those two alone give you pretty complete overview of the method and could lead you starting from the basics, up to pretty advanced topics.
If you don't know much on bootstrap yet I'll suggest starting with Efron & Tibshirani since it is written in a much simpler language and walks you through the topic step by step from the basics. Davison & Hinkley is a little bit tougher to read but provides you with many practical information and details. 
