Binomial probability

Results: 194



#Item
21Models of Insurance Claim Counts with Time Dependence Based on Generalization of Poisson and Negative Binomial Distributions by Jean-Philippe Boucher, Michel Denuit, and Montserrat Guillén

Models of Insurance Claim Counts with Time Dependence Based on Generalization of Poisson and Negative Binomial Distributions by Jean-Philippe Boucher, Michel Denuit, and Montserrat Guillén

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Source URL: www.variancejournal.org

Language: English - Date: 2008-06-30 10:20:05
22The Complete Mixability and Convex Minimization Problems with Monotone Marginal Densities Bin Wang∗ and Ruodu Wang† May 9, 2011  Abstract

The Complete Mixability and Convex Minimization Problems with Monotone Marginal Densities Bin Wang∗ and Ruodu Wang† May 9, 2011 Abstract

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Source URL: sas.uwaterloo.ca

Language: English - Date: 2011-05-09 10:28:41
23Answers	for	Q1	through	Q3	 	 Q1 a. Answer	is	greater	than	(i).

Answers for Q1 through Q3 Q1 a. Answer is greater than (i).

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Source URL: www-stat.wharton.upenn.edu

Language: English - Date: 2016-03-21 15:46:12
24Administrative Notes  StatisticsLecture 12 •  Homework 3 due in recitation on Friday, Feb. 26  Introduction to Inference

Administrative Notes StatisticsLecture 12 •  Homework 3 due in recitation on Friday, Feb. 26 Introduction to Inference

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Source URL: www-stat.wharton.upenn.edu

Language: English - Date: 2016-02-24 11:48:07
25Applied Probability Trust (13 DecemberADVANCES IN COMPLETE MIXABILITY GIOVANNI PUCCETTI,∗ University of Firenze BIN WANG,∗∗ Peking University RUODU WANG,∗∗∗ Georgia Institute of Technology

Applied Probability Trust (13 DecemberADVANCES IN COMPLETE MIXABILITY GIOVANNI PUCCETTI,∗ University of Firenze BIN WANG,∗∗ Peking University RUODU WANG,∗∗∗ Georgia Institute of Technology

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Source URL: sas.uwaterloo.ca

Language: English - Date: 2012-01-20 13:07:56
26Vida: How to use Bayesian inference to de-anonymize persistent communications George Danezis1 and Carmela Troncoso2 1  2

Vida: How to use Bayesian inference to de-anonymize persistent communications George Danezis1 and Carmela Troncoso2 1 2

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Source URL: www0.cs.ucl.ac.uk

Language: English - Date: 2013-10-10 06:48:53
27A Scaling Result for Explosive Processes M. Mitzenmacher   J. Spencer

A Scaling Result for Explosive Processes M. Mitzenmacher  J. Spencer

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Source URL: www.eecs.harvard.edu

Language: English - Date: 2002-07-08 11:27:45
28Further Optimal Regret Bounds for Thompson Sampling Navin Goyal  Microsoft Research India  arXiv:1209.3353v1 [cs.LG] 15 Sep 2012

Further Optimal Regret Bounds for Thompson Sampling Navin Goyal Microsoft Research India arXiv:1209.3353v1 [cs.LG] 15 Sep 2012

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Source URL: arxiv.org

Language: English - Date: 2012-09-17 20:29:44
29Tutorial on Pra
ti
al Predi
tion Theory for Classi
ation John Langford jlhun
h.net  Toyota Te
hnologi
al Institute at Chi
ago

Tutorial on Pra ti al Predi tion Theory for Classi ation John Langford jlhun h.net Toyota Te hnologi al Institute at Chi ago

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Source URL: hunch.net

Language: English - Date: 2006-12-03 12:48:21
30Categorical Data Analysis with Graphics  Unaided distant vision data 40 35

Categorical Data Analysis with Graphics Unaided distant vision data 40 35

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Source URL: www.datavis.ca

Language: English - Date: 2012-09-12 11:48:20