Conditional expectation

Results: 107



#Item
51Time Consistency Conditions for Acceptability Measures, with an Application to Tail Value at Risk Berend Roorda∗ Hans Schumacher†

Time Consistency Conditions for Acceptability Measures, with an Application to Tail Value at Risk Berend Roorda∗ Hans Schumacher†

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Source URL: doc.utwente.nl

Language: English - Date: 2011-08-28 10:49:32
52Finance Stochast. 10, 51–[removed]DOI: [removed]s00780[removed]c Springer-Verlag 2006 

Finance Stochast. 10, 51–[removed]DOI: [removed]s00780[removed]c Springer-Verlag 2006 

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Source URL: www.ise.ufl.edu

Language: English - Date: 2013-06-15 17:47:11
53Forecasting with Imprecise Probabilities Teddy Seidenfeld [removed] Mark J. Schervish [removed]

Forecasting with Imprecise Probabilities Teddy Seidenfeld [removed] Mark J. Schervish [removed]

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Source URL: www.hss.cmu.edu

Language: English - Date: 2012-03-27 09:39:55
54P1: FIC OJ002-04 April 12, [removed]:23

P1: FIC OJ002-04 April 12, [removed]:23

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Source URL: mqscores.berkeley.edu

Language: English - Date: 2014-07-14 18:26:26
55Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning Mengqiu Wang and Christopher D. Manning Computer Science Department Stanford University Stanford, CA[removed]USA

Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning Mengqiu Wang and Christopher D. Manning Computer Science Department Stanford University Stanford, CA[removed]USA

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Source URL: nlp.stanford.edu

Language: English - Date: 2014-07-16 02:05:44
56A BRIEF PRIMER ON CONDITIONAL EXPECTATION  Conditional expectation is a topic that I found somewhat obscure as a student. However there is really nothing to be afraid of. Let (X, F, µ) be a probability space (I have emp

A BRIEF PRIMER ON CONDITIONAL EXPECTATION Conditional expectation is a topic that I found somewhat obscure as a student. However there is really nothing to be afraid of. Let (X, F, µ) be a probability space (I have emp

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Source URL: people.maths.ox.ac.uk

Language: English - Date: 2013-08-05 12:58:15
57STAT 3050, CRN[removed]Introduction to Probability Theory and its Applications Winter 2014 Instructor:

STAT 3050, CRN[removed]Introduction to Probability Theory and its Applications Winter 2014 Instructor:

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Source URL: umanitoba.ca

Language: English - Date: 2013-11-13 13:09:23
58Surveillance Event Detection Mert Dikmen, Huazhong Ning, Dennis J. Lin, Liangliang Cao, Vuong Le, Shen-Fu Tsai, Kai-Hsiang Lin, Zhen Li, Jianchao Yang, Thomas S. Huang Department of Electrical and Computer Engineering Un

Surveillance Event Detection Mert Dikmen, Huazhong Ning, Dennis J. Lin, Liangliang Cao, Vuong Le, Shen-Fu Tsai, Kai-Hsiang Lin, Zhen Li, Jianchao Yang, Thomas S. Huang Department of Electrical and Computer Engineering Un

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Source URL: www-nlpir.nist.gov

Language: English - Date: 2009-05-18 11:26:55
59IDEAL Inference on Conditional Quantiles via Interpolated Duals of Exact Analytic L-statistics David M. Kaplan∗ Department of Economics, UC San Diego December 26, 2012; first version May 30, 2012

IDEAL Inference on Conditional Quantiles via Interpolated Duals of Exact Analytic L-statistics David M. Kaplan∗ Department of Economics, UC San Diego December 26, 2012; first version May 30, 2012

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Source URL: www.albany.edu

Language: English - Date: 2013-01-23 11:00:12
60Chapter 2. Review of basic Statistical methods 1 Distribution, conditional distribution and moments We consider two kinds of random variables: discrete and continuous random variables. For discrete random variable X, the

Chapter 2. Review of basic Statistical methods 1 Distribution, conditional distribution and moments We consider two kinds of random variables: discrete and continuous random variables. For discrete random variable X, the

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Source URL: www.math.mtu.edu

Language: English - Date: 2006-09-14 13:48:29