Self-Normalized Processes: Limit Theory and Statistical Applications (Probability and Its Applications) - Tapa blanda

Críticas

From the reviews:

"Readership: Research workers in applied probability. ... it serves as a reference text for a special-topic course for PhD students; each chapter after the first ends with a collection of problems and the material is based on such a course taught by two of the authors at Stanford and Hong kong. ... It is a thorough ... study of an area of applied probability that underlies important statistical methodology. ... I am sure that the text will encourage others to join them in their work." (Martin Crowder, International Statistical Review, Vol. 77 (3), 2009)

"The monograph will certainly be of great use as a reference text for researchers working on corresponding problems, but also for Ph.D. and other advanced students who want to learn about the techniques and relevant topics in an interesting and active research area. ... this monograph provides a very useful collection of recent and earlier research results in the theory and applications of self-normalized processes and can be used as a standard reference text by graduate students and researchers in the field." (Josef Steinebach, Zentralblatt MATH, Vol. 1165, 2009)

Reseña del editor

This volume covers recent developments in self-normalized processes, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales.