9781107020405 - A Basic Course in Measure and Probability: Theory for Applications by Leadbetter, Ross; Cambanis, Stamatis; Pipiras, Vladas (20 results)

Hardcover. Condition: New. No Jacket. 1st Edition. This is a new hardcover first edition copy, slick red binding, no DJ, 360 pages with index. Photos on request.

Condition: New.

Hardcover. Condition: new. Hardcover. Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery. This concise introduction covers all of the measure theory and probability most useful for statisticians. Originating from the authors' own graduate course, it is perfect for a two-term course or for self-study. It is especially useful to graduate students in related fields who want to shore up their mathematical foundation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. In.

Condition: New.

Hardcover. Condition: Brand New. 360 pages. 9.00x6.25x1.00 inches. In Stock.

Condition: New. 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. . . . .

Hardcover. Condition: Brand New. 360 pages. 9.00x6.25x1.00 inches. In Stock.

Condition: New. pp. 374 Index.

Condition: New. 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.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: new. Hardcover. Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery. This concise introduction covers all of the measure theory and probability most useful for statisticians. Originating from the authors' own graduate course, it is perfect for a two-term course or for self-study. It is especially useful to graduate students in related fields who want to shore up their mathematical foundation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This concise introduction covers all of the measure theory and probability most useful for statisticians. Originating from the authors own graduate course, it is perfect for a two-term course or for self-study. It is especially useful to graduate students .

Buch. Condition: Neu. A Basic Course in Measure and Probability | Theory for Applications | Ross Leadbetter (u. a.) | Buch | Gebunden | Englisch | 2014 | Cambridge University Press | EAN 9781107020405 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Condition: New. Print on Demand pp. 374 15 Illus.

Condition: New. PRINT ON DEMAND pp. 374 Acknowledgements.

Hardcover. Condition: new. Hardcover. Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery. This concise introduction covers all of the measure theory and probability most useful for statisticians. Originating from the authors' own graduate course, it is perfect for a two-term course or for self-study. It is especially useful to graduate students in related fields who want to shore up their mathematical foundation. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.