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SCIDIR_ocn876589188 |
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OCoLC |
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20231120111549.0 |
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m o d |
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cr cnu---unuuu |
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140414s2014 ne ob 001 0 eng d |
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|a OPELS
|b eng
|e rda
|e pn
|c OPELS
|d YDXCP
|d UKMGB
|d TEFOD
|d OCLCF
|d OCLCQ
|d TEFOD
|d OCLCQ
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|d D6H
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|d WYU
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|d LQU
|d OCLCQ
|d OCLCO
|d OCLCQ
|d OCLCO
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|a 016709723
|2 Uk
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|a 1105183531
|a 1105567426
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|a 9780128002902
|q (electronic bk.)
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|a 0128002905
|q (electronic bk.)
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|z 9780128000427
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|a (OCoLC)876589188
|z (OCoLC)1105183531
|z (OCoLC)1105567426
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|a QA273
|b .R864 2014eb
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0 |
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|a 519.2
|2 23
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|a Roussas, George G.,
|e author.
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|a An introduction to measure-theoretic probability /
|c by George G. Roussas.
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250 |
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|a Second edition.
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264 |
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|a Amsterdam ;
|a New York :
|b Academic Press, an imprint of Elsevier,
|c 2014.
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300 |
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|a 1 online resource
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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520 |
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|a "In this introductory chapter, the concepts of a field and of a [sigma]-field are introduced, they are illustrated bymeans of examples, and some relevant basic results are derived. Also, the concept of a monotone class is defined and its relationship to certain fields and [sigma]-fields is investigated. Given a collection of measurable spaces, their product space is defined, and some basic properties are established. The concept of a measurable mapping is introduced, and its relation to certain [sigma]-fields is studied. Finally, it is shown that any random variable is the pointwise limit of a sequence of simple random variables"--
|c Provided by publisher
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|a Includes bibliographical references and index.
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|a Print version record.
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|a Certain classes of sets, measurability, and pointwise approximation -- Definition and construction of a measure and its basic properties -- Some modes of convergence of sequences of random variables and their relationships -- The integral of a random variable and its basic properties -- Standard convergence theorems, the Fubini theorem -- Standard moment and probability inequalities, convergence in the rth mean and its implications -- The Hahn-Jordan decomposition theorem, the Lebesgue decomposition theorem, and the Radon-Nikodym theorem -- Distribution functions and their basic properties, Helly-Bray type results -- Conditional expectation and conditional probability, and related properties and results -- Independence -- Topics from the theory of characteristic functions -- The central limit problem: the centered case -- The central limit problem: the noncentered case -- Topics from sequences of independent random variables -- Topics from Ergodic theory -- Two cases of statistical inference: estimation of a real-valued parameter, nonparametric estimation of a probability density function -- Appendixes: A. Brief review of chapters 1-16 -- B. Brief review of Riemann-Stieltjes integral -- C. Notation and abbreviations.
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650 |
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|a Probabilities.
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650 |
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|a Measure theory.
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650 |
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6 |
|a Probabilit�es.
|0 (CaQQLa)201-0011592
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650 |
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|a Th�eorie de la mesure.
|0 (CaQQLa)201-0005696
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650 |
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7 |
|a probability.
|2 aat
|0 (CStmoGRI)aat300055653
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650 |
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7 |
|a Measure theory
|2 fast
|0 (OCoLC)fst01013175
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650 |
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7 |
|a Probabilities
|2 fast
|0 (OCoLC)fst01077737
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776 |
0 |
8 |
|i Print version:
|a Roussas, George G.
|t Introduction to measure-theoretic probability.
|b Second edition
|z 9780128000427
|w (DLC) 2014007243
|w (OCoLC)868642456
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856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128000427
|z Texto completo
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