A Basic Course in Measure and Probability: Theory for Applications

Ross Leadbetter

ISBN 10: 1107020409 / ISBN 13: 9781107020405

Editore: Cambridge University Press, 2014

Riguardo questo articolo

A concise introduction covering all of the measure theory and probability most useful for statisticians. Num Pages: 376 pages, 15 b/w illus. 300 exercises. BIC Classification: PBK; PBT. Category: (P) Professional & Vocational. Dimension: 232 x 161 x 22. Weight in Grams: 722. . 2014. Hardcover. . . . . Books ship from the US and Ireland.

Codice articolo V9781107020405

Dati bibliografici

• Titolo: A Basic Course in Measure and Probability: Theory for Applications
• Editore: Cambridge University Press
• Data di pubblicazione: 2014
• Lingua: Inglese
• ISBN 10: 1107020409
• ISBN 13: 9781107020405
• Rilegatura: Rilegato
• Condizione: New

Descrizione articolo

Riassunto

A concise introduction covering all of the measure theory and probability most useful for statisticians.

Informazioni sugli autori

Ross Leadbetter is Professor of Statistics and Operations Research at the University of North Carolina, Chapel Hill. His research involves stochastic process theory and applications, point processes, and particularly extreme value and risk theory for stationary sequences and processes.

Stamatis Cambanis was a Professor at the University of North Carolina, Chapel Hill until his death in 1995. He taught a wide range of statistics and probability courses and contributed very significantly to the development of the measure and probability instruction and the lecture notes on which this volume is based.

Vladas Pipiras has been with the University of North Carolina, Chapel Hill since 2002 and rose to full Professor in 2012. His main research interests focus on stochastic processes exhibiting long-range dependence, multifractality and other scaling phenomena, as well as on stable, extreme-value and other distributions possessing heavy tails. He has also worked on statistical inference questions for reduced-rank models with applications to econometrics, and sampling issues for finite point processes with applications to data traffic modeling in computer networks.