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作者 Leadbetter, Ross, author
書名 A basic course in measure and probability : theory for applications / Ross Leadbetter, University of North Carolina, Chapel Hill, Stamatis Cambanis, University of North Carolina, Chapel Hill, Vladas Pipiras, University of North Carolina, Chapel Hill
出版項 Cambridge ; New York : Cambridge University Press, 2014
國際標準書號 9781107020405 (hardback)
1107020409 (hardback)
9781107652521 (paperback)
1107652529 (paperback)
book jacket
館藏地 索書號 處理狀態 OPAC 訊息 條碼
 數學所圖書室  QC20.7.M43 L43 2014    在架上    30340200536724
 統計所圖書館圖書區I  QC20.7.M43 L43 2014    在架上    30570000134474
說明 xiv, 360 pages : illustrations ; 24 cm
text rdacontent
unmediated rdamedia
volume rdacarrier
附註 "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"-- Provided by publisher
Machine generated contents note: Preface; Acknowledgements; 1. Point sets and certain classes of sets; 2. Measures: general properties and extension; 3. Measurable functions and transformations; 4. The integral; 5. Absolute continuity and related topics; 6. Convergence of measurable functions, Lp-spaces; 7. Product spaces; 8. Integrating complex functions, Fourier theory and related topics; 9. Foundations of probability; 10. Independence; 11. Convergence and related topics; 12. Characteristic functions and central limit theorems; 13. Conditioning; 14. Martingales; 15. Basic structure of stochastic processes; References; Index
Includes bibliographical references (page 356) and index
主題 Measure theory
MATHEMATICS / Probability & Statistics / General. bisacsh
Maßtheorie. gnd
Wahrscheinlichkeitsrechnung. gnd
Wahrscheinlichkeitstheorie. gnd
Alt Author Cambanis, Stamatis, 1943-1995, author
Pipiras, Vladas, author
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