TY - BOOK ID - 14296037 TI - Self-normalized processes : limit theory and applications AU - De la Pea, Vctor H. AU - Lai, Tze Leung AU - Shao, Qi-Man. PY - 2009 SN - 3540856358 3642099262 9786611950965 1281950963 3540856366 PB - Berlin : Springer, DB - UniCat KW - Grenzwertsatz. KW - Limit theorems (Probability theory). KW - Mathematical statistics. KW - t-test (Statistics). KW - Limit theorems (Probability theory) KW - Mathematical statistics KW - t-test (Statistics) KW - Mathematics KW - Physical Sciences & Mathematics KW - Mathematical Statistics KW - Probabilities. KW - Statistical inference KW - Statistics, Mathematical KW - Probability KW - Statistical methods KW - Mathematics. KW - Statistics. KW - Probability Theory and Stochastic Processes. KW - Statistical Theory and Methods. KW - Combinations KW - Chance KW - Least squares KW - Risk KW - Statistics KW - Probabilities KW - Sampling (Statistics) KW - Distribution (Probability theory. KW - Distribution functions KW - Frequency distribution KW - Characteristic functions KW - Statistics . KW - Statistical analysis KW - Statistical data KW - Statistical science KW - Econometrics UR - https://www.unicat.be/uniCat?func=search&query=sysid:14296037 AB - Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference. The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization. ER -