Isbn: 9781107652521 - a basic course in measure and probability: theory for applications (5 résultats)

paperback. Etat : Very Good.

Paperback. Etat : new. Paperback. 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.…

Paperback. Etat : Brand New. 360 pages. 8.75x6.00x0.75 inches. In Stock.

Etat : gut. A Basic Course in Measure and Probability: Theory For Applications In englischer Sprache. pages.

Etat : 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 .…