標(biāo)題: Titlebook: An Introduction to Copulas; Roger B. Nelsen Book 19991st edition Springer Science+Business Media New York 1999 Parametric statistics.mathe [打印本頁] 作者: 威風(fēng) 時(shí)間: 2025-3-21 19:48
書目名稱An Introduction to Copulas影響因子(影響力)
書目名稱An Introduction to Copulas影響因子(影響力)學(xué)科排名
書目名稱An Introduction to Copulas網(wǎng)絡(luò)公開度
書目名稱An Introduction to Copulas網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱An Introduction to Copulas被引頻次
書目名稱An Introduction to Copulas被引頻次學(xué)科排名
書目名稱An Introduction to Copulas年度引用
書目名稱An Introduction to Copulas年度引用學(xué)科排名
書目名稱An Introduction to Copulas讀者反饋
書目名稱An Introduction to Copulas讀者反饋學(xué)科排名
作者: BRAWL 時(shí)間: 2025-3-21 20:19 作者: 軌道 時(shí)間: 2025-3-22 04:05
https://doi.org/10.1007/978-3-642-48438-4the nonparametric nature of the dependence between two random variables, is expressed by the copula. Thus the study of concepts and measures of nonparametric dependence is a study of properties of copulas—a topic we will pursue in Chapter 5. For this study, it is advantageous to have a variety of copulas at our disposal.作者: CAGE 時(shí)間: 2025-3-22 06:34 作者: LITHE 時(shí)間: 2025-3-22 11:33
Archimedean Copulas,t rather in the study of probabilistic metric spaces, where they were studied as part of the development of a probabilistic version of the triangle inequality. For an account of this history, see [Schweizer (1991)] and the references cited therein.作者: Herpetologist 時(shí)間: 2025-3-22 16:39 作者: dandruff 時(shí)間: 2025-3-22 19:01
Book 19991st editions is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the作者: 占線 時(shí)間: 2025-3-22 23:57
Die Rasse-Intelligenz-Kontroverse,t rather in the study of probabilistic metric spaces, where they were studied as part of the development of a probabilistic version of the triangle inequality. For an account of this history, see [Schweizer (1991)] and the references cited therein.作者: 哺乳動(dòng)物 時(shí)間: 2025-3-23 03:42
,Soziale Reaktionen auf Unmündigkeit,following. In studying “distances” between distributions, Dall’Aglio (1956, 1991) considered the following problem (see Exercise 6.5): What is the minimum value of .given that the margins of . are fixed to be . and .,respectively?作者: epinephrine 時(shí)間: 2025-3-23 05:31 作者: Decibel 時(shí)間: 2025-3-23 11:53
Definitions and Basic Properties,tribution functions” and as “distribution functions whose one-dimensional margins are uniform.” But neither of these statements is a definition—hence we will devote this chapter to giving a precise definition of copulas and to examining some of their elementary properties.作者: 匯總 時(shí)間: 2025-3-23 15:37
Methods of Constructing Copulas,tions with whatever marginal distributions we desire. Clearly this can be useful in modeling and simulation. Furthermore, by virtue of Theorem 2.4.3, the nonparametric nature of the dependence between two random variables, is expressed by the copula. Thus the study of concepts and measures of nonpar作者: novelty 時(shí)間: 2025-3-23 18:20 作者: theta-waves 時(shí)間: 2025-3-24 01:00 作者: 受傷 時(shí)間: 2025-3-24 04:47
Additional Topics,the subject. The original question whose answer leads to the Fréchet-Hoeffding bounds (2.5.1) is: Of all joint distribution functions . constrained to have . and ., which is the “l(fā)argest,” and which the “smallest”? Another example, which also involves optimization when the margins are fixed, is the 作者: set598 時(shí)間: 2025-3-24 07:09
https://doi.org/10.1007/978-3-642-48438-4tribution functions” and as “distribution functions whose one-dimensional margins are uniform.” But neither of these statements is a definition—hence we will devote this chapter to giving a precise definition of copulas and to examining some of their elementary properties.作者: Tractable 時(shí)間: 2025-3-24 11:04
https://doi.org/10.1007/978-3-642-48438-4tions with whatever marginal distributions we desire. Clearly this can be useful in modeling and simulation. Furthermore, by virtue of Theorem 2.4.3, the nonparametric nature of the dependence between two random variables, is expressed by the copula. Thus the study of concepts and measures of nonpar作者: 谷類 時(shí)間: 2025-3-24 16:35
Die Rasse-Intelligenz-Kontroverse, reasons: (1) The ease with which they can be constructed; (2) The great variety of families of copulas which belong to this class; and (3) The many nice properties possessed by the members of this class. As mentioned in the Introduction, Archimedean copulas originally appeared not in statistics, bu作者: 使高興 時(shí)間: 2025-3-24 21:36 作者: 狗窩 時(shí)間: 2025-3-25 02:19
,Soziale Reaktionen auf Unmündigkeit,the subject. The original question whose answer leads to the Fréchet-Hoeffding bounds (2.5.1) is: Of all joint distribution functions . constrained to have . and ., which is the “l(fā)argest,” and which the “smallest”? Another example, which also involves optimization when the margins are fixed, is the 作者: tympanometry 時(shí)間: 2025-3-25 06:06
https://doi.org/10.1007/978-1-4757-3076-0Parametric statistics; mathematical statistics; mathematics; probability; statistics; quantitative financ作者: 饑荒 時(shí)間: 2025-3-25 08:13
Springer Science+Business Media New York 1999作者: 業(yè)余愛好者 時(shí)間: 2025-3-25 13:45 作者: nerve-sparing 時(shí)間: 2025-3-25 17:19
Dependence,s,.“Dependence relations between random variables is one of the most widely studied subjects in probability and statistics. The nature of the dependence can take a variety of forms and unless some specific assumptions are made about the dependence, no meaningful statistical model can be contemplated.”作者: flutter 時(shí)間: 2025-3-25 23:17
Lecture Notes in Statisticshttp://image.papertrans.cn/a/image/155198.jpg作者: Geyser 時(shí)間: 2025-3-26 03:15
An Introduction to Copulas978-1-4757-3076-0Series ISSN 0930-0325 Series E-ISSN 2197-7186 作者: 演繹 時(shí)間: 2025-3-26 07:14 作者: 發(fā)酵劑 時(shí)間: 2025-3-26 11:13
Sozialisation und Organisationswirklichkeit,s,.“Dependence relations between random variables is one of the most widely studied subjects in probability and statistics. The nature of the dependence can take a variety of forms and unless some specific assumptions are made about the dependence, no meaningful statistical model can be contemplated.”作者: 評(píng)論性 時(shí)間: 2025-3-26 16:02
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