Holdings: Measure-Theoretic Probability

Measure-Theoretic Probability: With Applications to Statistics, Finance, and Engineering

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Bibliographic Details
Main Author:	Shum, Kenneth (Author)
Format:	Electronic eBook
Language:	English
Published:	Cham Springer International Publishing 2023 Cham Birkhäuser
Edition:	1st ed. 2023
Series:	Compact Textbooks in Mathematics
Subjects:	Probability Theory Applied Probability Measure and Integration Probabilities Measure theory
Online Access:	BTU01 FHD01 FHN01 FHR01 FRO01 FWS01 FWS02 HTW01 TUM01 UBM01 UBT01 UBW01 UBY01 UEI01 UPA01 Volltext
Physical Description:	1 Online-Ressource (XV, 259 p. 33 illus., 25 illus. in color)
ISBN:	9783031498305
ISSN:	2296-455X
DOI:	10.1007/978-3-031-49830-5

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MARC


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Record in the Search Index

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publisher	Springer International Publishing Birkhäuser
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series2	Compact Textbooks in Mathematics
spellingShingle	Shum, Kenneth Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering Probability Theory Applied Probability Measure and Integration Probabilities Measure theory
title	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering
title_auth	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering
title_exact_search	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering
title_exact_search_txtP	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering
title_full	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering by Kenneth Shum
title_fullStr	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering by Kenneth Shum
title_full_unstemmed	Measure-Theoretic Probability With Applications to Statistics, Finance, and Engineering by Kenneth Shum
title_short	Measure-Theoretic Probability
title_sort	measure theoretic probability with applications to statistics finance and engineering
title_sub	With Applications to Statistics, Finance, and Engineering
topic	Probability Theory Applied Probability Measure and Integration Probabilities Measure theory
topic_facet	Probability Theory Applied Probability Measure and Integration Probabilities Measure theory
url	https://doi.org/10.1007/978-3-031-49830-5
work_keys_str_mv	AT shumkenneth measuretheoreticprobabilitywithapplicationstostatisticsfinanceandengineering

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