The field of mathematical statistics called robustness statistics dealswith the stability of statistical inference under variations of accepteddistribution models. Although robust statistics involves mathematicallyhighly defined tools, robust methods exhibit a satisfactory behaviour insmall samples, thus being quite useful in applications.
This volume in the book series Modern Probability andStatistics addresses various topics in the field of robust statisticsand data analysis, such as: a probability-free approach in dataanalysis; minimax variance estimators of location, scale, regression,autoregression and correlation; L1-norm methods; adaptive, datareduction, bivariate boxplot, and multivariate outlier detectionalgorithms; applications in reliability, detection of signals, andanalysis of the sudden cardiac death risk factors.
The book contains new results related to robustness and data analysistechnologies, including both theoretical aspects and practical needs ofdata processing, which have been relatively inaccessible as they wereoriginally only published in Russian.
This book will be of value and interest to researchers in mathematicalstatistics as well as to those using statistical methods.
2001; xiv+310 pages ISBN 90-6764-351-3 Price (all prices are subject to change without notice): EUR 152/US$ 217
