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Titlebook: Probability Theory; Independence, Interc Yuan Shih Chow,Henry Teicher Textbook 19882nd edition Springer-Verlag New York Inc. 1988 Martingal

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书目名称Probability Theory
副标题Independence, Interc
编辑Yuan Shih Chow,Henry Teicher
视频videohttp://file.papertrans.cn/757/756891/756891.mp4
丛书名称Springer Texts in Statistics
图书封面Titlebook: Probability Theory; Independence, Interc Yuan Shih Chow,Henry Teicher Textbook 19882nd edition Springer-Verlag New York Inc. 1988 Martingal
描述Apart from new examples and exercises, some simplifications of proofs, minor improvements, and correction of typographical errors, the principal change from the first edition is the addition of section 9.5, dealing with the central limit theorem for martingales and more general stochastic arrays. vii Preface to the First Edition Probability theory is a branch of mathematics dealing with chance phenomena and has clearly discernible links with the real world. The origins of the sub­ ject, generally attributed to investigations by the renowned French mathe­ matician Fermat of problems posed by a gambling contemporary to Pascal, have been pushed back a century earlier to the Italian mathematicians Cardano and Tartaglia about 1570 (Ore, 1953). Results as significant as the Bernoulli weak law of large numbers appeared as early as 1713, although its counterpart, the Borel strong law oflarge numbers, did not emerge until 1909. Central limit theorems and conditional probabilities were already being investigated in the eighteenth century, but the first serious attempts to grapple with the logical foundations of probability seem to be Keynes (1921), von Mises (1928; 1931), and Kolmogorov (193
出版日期Textbook 19882nd edition
关键词Martingal; Martingale; Maxima; Probability theory; Random variable; conditional probability; law of the it
版次2
doihttps://doi.org/10.1007/978-1-4684-0504-0
isbn_softcover978-1-4684-0506-4
isbn_ebook978-1-4684-0504-0Series ISSN 1431-875X Series E-ISSN 2197-4136
issn_series 1431-875X
copyrightSpringer-Verlag New York Inc. 1988
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978-1-4684-0506-4Springer-Verlag New York Inc. 1988
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Sums of Independent Random Variables,e i.i.d. is of especial interest and frequently lends itself to more incisive results. The sequence of sums {.., n ≥ 1} of i.i.d. r.v.s {..} is alluded to as a random walk; in the particular case when the component r.v.s {..} are nonnegative, the random walk is referred to as a renewal process.
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Binomial Random Variables,The major theorems of probability theory fall into a natural dichotomythose which are analytic in character and those which are measure-theoretic. In the latter category are zero—one laws, the Borel—Cantelli lemma, strong laws oflarge numbers, and indeed any result which requires the apparatus of a probability space.
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Measure Extensions, Lebesgue-Stieltjes Measure Kolmogorov Consistency Theorem,A salient underpinning of probability theory is the one-to-one correspondence between distribution functions on .. and probability measures on the Borel subsets of ... Verification of this correspondence involves the notion of measure extension.
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