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    • 概率论(第2卷第4版影印版)(英文版)
      • 作者:(美)M.洛易甫
      • 出版社:世界图书出版公司
      • ISBN:9787519255794
      • 出版日期:2019/03/01
      • 页数:413
    • 售价:47.6
  • 内容大纲

        本书被公认为是一套概率论方面的标准经典教科书,供高年级大学生和研究生使用,同时也是概率论和统计学方面研究人员经常使用的参考书。本书把概率论建立在严格的逻辑基础上,理论体系完整。第2卷包括两部分内容,涉及条件运算及独立随机变量和极限性质的相依性、二阶随机函数、随机分析的基本概念以及鞅、可分解性、随机函数的马尔可夫型等。读者对象:数学及相关专业的研究生。
  • 作者介绍

  • 目录

    PART FOUR: DEPENDENCE
      CHAPTER Ⅷ: CONDITIONING
        27. CONCEPT OF CONDITIONING
        27.1  Elementary case
        27.2  General case
        27.3  Conditional expectation given a function
        *27.4  Relative conditional expectations and sufficient
        σ-fiields
        28. PROPERTIES OF CONDITIONING
        28.1  Expectation properties
        28.2  Smoothing properties
        *28.3  Concepts of conditional independence and of chains
        29. REGULAR PR. FUNCTIONS
        29.1  Regularity and integration
        *29.2  Decomposition of regular c.pr.'s given separable
        a-fields
        30. CONDITIONAL DISTRIBUTIONS
        30.1  Definitions and restricted integration
        30.2  Existence.
        30.3  Chains; the elementary case
        COMPLEMENTS AND DETAILS
      CHAPTER Ⅸ: FROM INDEPENDENCE TO DEPENDENCE
        31. CENTRAL ASYMPTOTIC PROBLEM
        31.1  Comparison of laws
        31.2  Comparison of summands
        "31.3  Weighted prob. laws
        32. CENTERINGS, MARTINGALES, AND A.$. CONVERGENCE
        32.1  Centerings
        32.3  Martingales: generalities
        32.3  Martingales: convergence and closure
        32.4  Applications
        *32.5  Indefinite expectations and a.s. convergence
        COMPLEMENTS  AND  DETAILS
      CHAPTER  Ⅹ:   ERGODIC  THEOREMS
        33. TRANSLATION OF SEQUENCES; BASIC ERGODIC THEOREM AN
        STATIONA RITY
        *33.1  Phenomenological origin
        33.2  Basic ergodic inequality
        33.3  Stationarity
        33.4  Applications; ergodic hypothesis and independence
        *33.5  Applications; stationary chains
        *34. ERGODIC THEOREMS AND Lt-SPACES
        *34.1  Translations and their extensions
        *34.2  A.s. ergodic theorem
        *34.3  Ergodic theorems on spaces L
        *35. ERGODIC THEOREMS ON BANACH SPACES
        *35.1  Norms crgodic theorem
        *35.2  Uniform norms ergodic theorems
        *35.3  Application to constant chains
        COMPLEMENTS AND DETAILS

      CHAPTER Ⅺ SECOND ORDER PROPERTIES
        36. ORTHOGONALITY
        36.1  Orthogonal r.v.'s; convergence and stability
        36.2  Elementary orthogonal decomposition
        36.3  Projection, conditioning, and normality
        37. SECOND ORDER RANDOM FUNCTIONS
        37.1  Covarianccs
        37.2  Calculus in q.m.; continuity and differentiation
        37.3  Calculus in q.m.; integration
        37.4  Fourier-Stichjes transforms in q.m.
        37.5  Orthogonal decompositions
        37.6  Normality and almost-sure properties
        37.7  A.s. stability
        COMPLEMENTS AND DETAILS
    PART FIVE: ELEMENTS OF RANDOM ANALYSIS
      CHAPTER Ⅻ: FOUNDATIONS; MARTINGALES AND DECOMPOSABILITY
        38. FOUNDATIONS
        38.1  Generalities
        38.2  Separability
        38.3  Sample continuity
        38.4  Random times
        39. MARTINGALES .
        39.1  Closure and limits
        39.2  Martingale times and stopping
        40. DECOMPOSABILITY
        40.1  Generalities
        40.2  Three parts decomposition
        40.3  Infinite decomposability; normal and Poisson cases
        COMPLEMENTS AND DETAILS
      CHAPTER ⅩⅢ: BROWNIAN MOTION AND LIMIT DISTRIBUTIONS
        41. BROWNIAN MOTION
        41.1  Origins
        41.2  Definitions and relevant properties
        41.3  Brownian sample oscillations
        41.4  Brownian times and functionals
        42. LIMIT DISTRIBUTIONS
        42.1  Pr.'son
        42.2  Limit distributions on e.
        42.3  Limit distributions; Brownian embedding
        42.4  Some specific functionals
        Complements and Details
      CHAPTER ⅩⅣ MARKOV PROCESSES
        43. MARKOV DEPENDENCE
        43.1  Markov property
        43.2  Regular Markov processes
        43.4  Stationarity
        43.4  Strong Markov property
        44. TIME-CONTINUOUS TRANSITION PROBABILITIES
        44.1  Differentiation of tr. pr.'s
        44.2  Sample functions behavior

        45. MARKOV SEMI-GROUPS
        45.1  Generalities
        45.2  Analysis of semi-groups
        45.3  Markov processes and semi-groups
        46. SAMPLE CONTINUITY AND DIFFUSION OPERATORS
        46.1  Strong Markov property and sample rightcontinuity
        46.2  Extended infinitesimal operator
        46.3  One-dimensional diffusion operator
    COMPLEMENTS  AND  DETAILS
    BIBLIOGRAPHY
    INDEX

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