Sampling Algorithms / Springer Series in Statistics (PDF)

From the reviews:

"As well as containing much new material, the book succeeds in providing a systematic development for what often seems a collection of isolated and ad hoc methods." A.J. Scott for Short Book Reviews of the ISI, December 2006

"This book draws up an inventory of new methods that can be useful for selecting samples. … The book is well-organized and lucidly written. It maintains a very high level of mathematical rigor and, at the same time, its contents have direct practical applicability. The numerous examples as well as the extensive list of references will endear it to the readers. Overall, this is an outstanding book which will be of great value to anyone interested in the theory of survey sampling." (Rahul Mukerjee, Zentralblatt MATH, Vol. 1099 (1), 2007)

"This book is a state-of-the-art of sampling techniques different from ‘order sampling’, and its author takes this opportunity to clarify his own points of view and contribution to the topic, mainly with some emphasis on joint inclusion probabilities and the use of the so-called cube method to select balanced samples. … Forty-six algorithms are described. The book is clear, easy to read and could be used as a textbook to teach the topic … ." (Guy Jumarie, Mathematical Reviews, Issue 2007 c)

"A comprehensive overview of … sampling algorithms, in a very clear and comprehensible way. The concise presentation of many sampling algorithms enables interested practitioners to easily apply or implement the methods in their own programs. … All readers will find the list of algorithms, abbreviations, and notation very useful. … Personally, I feel that this book is a must for any survey researcher interested in sample selection procedures. It should be of great interest for practitioners who need to implement surveys … ." (Ralf Munnich, Journal of the American Statistical Association, Vol. 103 (481), 2008)