Asymptotic distribution theorems in probability and statistics have, from the beginning, depended on the classical theory of weak convergence of distribution functions in Euclidean space. The past several decades have seen the creation and extensive application of a more inclusive theory of weak convergence of probability measures on metric spaces.
Im Mittelpunkt dieses Buches stehen langsam konvergierende Methoden in metrischen Räumen, deren Fähigkeiten und Nutzen anhand zahlreicher Beispiele vorgeführt werden. Die überarbeitete 2. Auflage enthält jetzt auch Angaben zu Unterräumen, dem Skorohodschen Darstellungstheorem, der Prohorov-Metrik und dem Poisson-Limit. (09/99)
The book is a classic [...]. (The Statistician, 49 (3), 2000)
...it seems destined to become another clasic and is of interest even to those who already own the first edition. (Zentralblatt Math, Volume 944, No. 19, 2000)
"...the author may be congratulated. The book will definitely maintain and extend its role as a fundamental introduction and contribution to the subject." (Statistics & Decisions, Vol. 18/3, 2000)
