1. Smithsonian Institute. Vote: The Machinery of Democracy. [Online]
0 0, 2004. [Cited: September 16, 2006.]
http://americanhistory.si.edu/vote/votingmachine.html.
2. Jones, Douglas W. Douglas W. Jones
Illustrated Voting Machines History. [Online] 2003. [Cited: January 15, 2005.] http://www.cs.uiowa.edu/~jones/voting/pictures/#punchcard.
3. Election Data Services, Inc. 2004 Election Day Survey Report. Washington
DC : Election Assistance Commission, 2005. EAC Requested Consultaion
Services Report.
4. Kohno, Tadayoshi, Stubblefield, Adam and
Rubin, Aviel D. Analysis of an Electronic Voting System. s.l. :
IEEE Computer Society Press, 2004. IEEE Symposium on Security and Privacy.
5. U.S. Department of Defense Federal Voting
Assistance Program. eVoting Initiatives. [Online] December 2005. [Cited:
September 22, 2006.] http://www.fvap.gov/services/evoting.html.
6. GAO. Federal Efforts to Improve Security and Reliability of Electronic
Voting Systems are Under Way, but Key Activities Need to Be Completed. s.l. :
Government Accountability Office, September, 2005. p. 102, Report to
Congressional Requester. GAO-05-956.
7. Gritzalis, Dimitris. Secure Electronic Voting. s.l. :
Springer, 2003. 978-1-4020-7301-4.
8. Damgard, Ivan, Jurik, Mads and Nielsen,
Jesper Buus. A Generalizion of Pallier's Public-Key System with
Applications to Electronic Voting. Lecture
Notes in Computer Science. s.l. : Springer Verlag, 2003, Vol. 1992,
pp. 119 - 136.
9. Baudron, O., et al. Practical Multi-Candidate Election System. New
Port : ACM Press, 2001. ACM Sympossium on Principles of Distributed
Computing. pp. 274-283.
10. Boneh, Dan and Golle, Philippe. Almost Entirely Correct Mixing with
Applications to Voting. Washington DC : ACM Press, 2002. CSC '02.
11. Cramer, Ronald, Gennaro, Rosario and
Schoenmakers, Berry. [ed.] Walter Fumy.
A Scenario and Optimally
Efficient Multi-Authority Election Scheme. Berlin Heidelberg :
Springer-Verlag, 1997. EUROCRYPT '97. pp. 103-118.
12. The Open Group. The Open Group
Architectural Framework. The Open
Group. [Online] 8.1, December 19, 2003. [Cited: January 15, 2004.] URL :
http://www.opengroup.org/pubs. http://www.opengroup.org/pub.
13. Zachman, John A. A
framework for Information System Architecture. 3, s.l. : IBM, 1987,
IBM Systems Journal, Vol. 26, pp. 276 - 296.
14. Sowa, J. F and Zachman, A. J. Extending
and Formalizing the framework for Information System Architecture. 3,
1992, IBM System Journal, Vol. 31, pp. 590 - 616.
15. Heaney, Jody. Security
for Enterprise Engineering : Weathering Storms. 2, Washington DC :
MITRE Corporation, 2003, Vol. 7.
16. The Open Group. The Open Group Architectural Framework. s.l. :
The Open Group, 2003.
17. The US Department of Defense. DoD
Architectural Framework version 1.0 Volume 1: Definition and Guidelines. 1
s.l. : US Department of Defense, February 9, 2004. Vol. 1.
18. US Department of Defense. Department of Defense Trusted Computer
System Evaluation Criteria. s.l. : Department of Defense, 1985.
Department of Defense Standard. DoD 5200.28-STD.
19. US-NIST, et al. Common Criteria. 2005.
20. Gollmann, Dieter, Massacci, Fabio and
Yautsiukhin, Artsiom. Quality
of Protection: Security Measurements and Metrics. s.l. : Springer,
2006. 0-387-29016-8.
21. Casola, Valentino, et al. A SLA
evaluation methodology in Service Oriented Architectures. [ed.] Dieter
Gollmann, Fabio Massacci and Artsiom Yautsiukhim. Quality of Protection, Security Measurements and Metrics. s.l. :
Springer, 2006, pp. 119 - 130.
22. Lundin, Reine, et al. Using Guesswork
as a Measure for Confidentilality for Selectively Encrypted Messages. [ed.]
Dieter Gollmann, Fabio Massacci and Artsiom Yautsiukhin. Quality of Protection, Security Measurements
and Metrics. s.l. : Springer, 2006, pp. 173 - 184.
23. Atzeni, Andrea and Torino, Antonio.
Why to adopt a security metric? A brief Survey. [book auth.] Dieter Gollmann,
Fabio Massacci and Artsiom Yautsiukhim. Quality
of Protection, Security Measurements and Metrics. s.l. : Springer,
2006, pp. 1 -12.
24. Fair Isaac Corporation. A discussion
of Data Analysis, Prediction and Decision Techniques. s.l. : Fair Isaac
Corporation, 2004.
25. Albanese, Claudio and Campolieti, Guiseppe.
Advanced Derivatives Pricing and Risk
Management, Theory , Tools , and Hands-On Programming Applications. Burlington :
Elsevier Academic Press, 2006.
26. Fine, Terrence L. Probability and Probabilistic Reasoning for
Electrical Engineering. New Jersey : Prentice Hall, 2006.
780-130-205919.
27. Clemen, Robert T and Reilly, Terence. Correlations and Copulas for Decision and
Risk Analysis. 2, s.l. : Institute of Operational Research and
Management Sciences, February 1999, Management Science, Vol. 45, pp. 208 - 224.
28. Zachman, John A. A framework for Information System
Architecture. 3, s.l. : IBM, 1987, IBM Systems Journal, Vol. 26,
pp. 276-292.
29. Vicente, Aceituno, Canal. Information Security Management Maturity
Model. s.l. : Institute of Security and Open Methodologies, 2005.
30. Institute, IT Governance. ISACA. http://www.itgi.org. [Online] 4.0,
January 9, 2006. [Cited: January 12, 2006.] http://www.isaca.org.
31. Hansche, Susan, Berti, John and Hare, Chris.
Official (ISC)2 Guide to the CISSP
Exam. s.l. : Auerbach Publications, 2004. 0-8493-1707-X.
32. Zhao, Houlin. Security in Telecommunications and Information Technology. International
Telecommunications Union. Geneva : International Telecommunications Union,
December 2003. p. 89, An ITU-T X Series Manual.
33. The European Parliament and The Council of
European Union. Official Journal of the European Communities. Europa. [Online] July 31, 2002.
[Cited: February 13, 2007.]
http://europa.eu.int/eur-lex/pri/en/oj/dat/2002/l_201/l_20120020731en00370047.pdf.
34. US Department of Justics. USDOJ : FOAI
: Overview of the Privacy Act of 1974. USDOJ.
[Online] [Cited: February 13, 2007.]
http://www.usdoj.gov/oip/04_7_1.html.
35. Zou, Cliff Changchun, et al. Monitoring
and Early Warning for Internet Worms. Washington DC : ACM, 2003.
36. Hall, David L. and McMullen, Sonya A. H.
Mathematical Techniques in Multisensor
Data Fusion. Second. Norwood : Artech House, 2004. 1-58053-335-3.
37. Asante-Duah, Kofi, D. Hazardous Waste Risk Management. Florida :
Lewis Publishers, 1993. 0-87371-570-5.
38. Wikipedia. Measure. Wikipedia. [Online]
http://en.wikipedia.org/wiki/Measure_theory.
39. Dudley, R M. Real Analysis and Probability. New York : Cambridge
University Press, 2002.
40. Feller, William. An Introduction to Probability Theory and
Its Applications. Princton : John Wiley & Sons, 1970. Vol. II.
780-471-257097.
41. Parker, Tom, et al. Stealing The Network : How to own a
continent. [ed.] Kevin Mitnick. Rockland : Syngress, 2004.
1-931836-05-1.
42. Swanson, Marianne, et al. Security Metrics Guide for Information
Technology Systems. Computer Security, NIST ITL. Gaithersburg :
National Institute of Science and Technology, 2003. NIST Special Publication.
SP 800-55.
43. GAO. Information Security : Department of Homeland Sceurity faces Challenges
in fulfilling Statutory Requirements. United States Government
Accountability Office. Washington DC : US Government Accountability
Office, 2005. Statement of The Director, Gregory C. Wilshusen. GAO-05-567T.
44. aughn, Rayford B, Henning, Ronda and Siraj,
Ambareen. Information Assurance
Measures and Metrics - State of Practice and Proposed Taxonomy. V s.l. : IEEE, 2002. Proceedings
of the 36th Hawai International Conferences on System Sciences.
0-7695-1874-5/03.
45. JP Morgan. RiskMetrics - Technical
Document. Fourth [ed.] Jacques Longerstae and Martin Spencer. New York :
Morgan Guarantee Trust Company of New York, 1996.
46. Artzner, Philippe, et al. Coherent Measure of Risk. 3,
s.l. : Blackwell Publishing, July 1999, Mathematical Finance, Vol. 9, pp.
203 - 228.
47. Gordy, Michael B. A Comparative Anatomy of Credit Risk Models.
1998.
48. Luciano, Elisa. Credit Risk Assesment Via Copulas :
Association Invariance and Risk Neutrality. 2005.
49. Burtschell, Xavier, Gregory, Jon and Laurent,
Jean Paul. Beyond Gaussian Copula : Stochastic and
Local Correlation. s.l. : American Economic Association, 2005,
Journal of Economic Literature.
50. Zivot, Eric and Wang, Jiahui. Modeling Financial Time Series With S-Plus. s.l. :
Springer Science+Business Media, Inc., 2006. 0-387-27965-2.
51. Schonbucher, Philipp J and Schubert, Dirk.
Copula-Dependent Default Risk in Intensity Models. 2001.
52. Coronado, Maria. Comparing Different
Methods for Estimating Vale at Risk(VaR) for Actual Non-Linear Portfolios:
Emperical Evidence. European Journal
of Finance. 2000.
53. Coronado, Maria. Extreme Value Theory(EVT) for Risk Managers:
Pitfalls and Opportunities in the Use of EVT in Measuring VaR. Department
of Finance, ICADE. Universidad P. Comillas de Madrid. 2002. pp. 1 - 32,
Conference Presentation : 5th SGF Conference. Source : http://www.fmpm.ch/docs/5th.htm.
54. Embrechts, Paul, Lindskog, Filip and McNeil,
Alexander. Modeling Dependence
with Copulas and Applications to Risk Management. 2001.
55. Nelsen, Roger B. Properties
and Applications of copulas: A brief survey.
56. Shannon, Claude E. A Mathematical
Theory of Communication. The Bell
System Technical Journal. 1948, Vol. 27, pp. 379 - 423, 623 - 656. A
Reprint Version.
57. Cover, Thomas M and Thomas, Joy A. Elements of Information Theory. s.l. :
John Wiley & Sons, 1991. Elements of Information Theory.
58. Joe, Harry. Majorization, Randomness
and Dependence for Multivariate Distributions. The Annals of Probability. 1987, Vol. 15, 3.
59. Joe,
Harry. Majorization, Entropy and Paired Comparisons. The Annals of Statistics. June 1988, Vol. 16, 2.
60. de la Pena Victor H., Ibragimov Rustam,
Sharakhmetov Shaturgun. Characterization
of joint distributions, copulas, information, dependence and decoupling, with
applications to time series. s.l. : Institute of Mathematical
Statistics, 2006. IMS Lecture Notes -Monograph Series - 2nd Lehmann Symposium -
Optimality. Vol. 49. 183-209.
61. Joe, Harry. Relative Entropy Measures
of Multivariate Dependence. Journal of
American Statistical Association. March 1989, Vol. 84, 405, pp. 157 -
164.
62. Natrella, M. Extreme Value
Distribution. [book auth.] National Institute of Science and Technology. Engineering Statistics Handbook. s.l. :
NIST, 2006, pp. 2930 - 2933.
63. The Mathworks, Inc. Statistics Toolbox Manual. s.l. :
The Mathworks Inc., 2006.
64. Weisstein, Eric W. Extreme Value
Distribution. MathWorld. [Online]
March 24, 2006. [Cited: June 22, 2006.]
http://mathworld.wolfram.com/ExtremeValueDistribution.html.
65. Wikipedia. Generalized Extreme Value
Distribution. Wikipedia. [Online]
[Cited: 10 02, 2006.]
http://en.wikipedia.org/wiki/Generalized_extreme_value_distribution.
66. Armstrong, Margaret and Galli, Alain.
Sequential Nongaussian Simulation Using FGM Copula. September 18, 2002.
67. Cuvelier, Etienne and Noirhomme-Fraiture,
Monique. Clayton copula and
mixture decomposition. Brest : ASMDA, 2005. Applied Stochastic
Models and Data Analysis (ASMDA). pp. 699 -708.
68. US Department of State. Rights of the
People : Individual Freedom and The Bill of Rights. US department of State International Information Programs. [Online]
http://usinfo.state.gov/products/pubs/rightsof/vote.htm.
69. EAC TGDC. Voluntary Voting System Guidelines. Gaithesburge : Election
Assistance Commission, EAC, 2005. p. 206, Technical Guidelines.
70. Maryland Board of Elections. Voting
Systems : Maryland Board of Elections. Maryland
Board of elections. [Online] Maryland Board of Elections, March 16,
2006. [Cited: January 26, 2007.]
http://sbe2.elections.state.md.us/citizens/voting_systems/index.html.
71. Feldman, Ariel J, Halderman, Alex J and
Felten, Edward W. Security
Analysis of the Diebold AccuVote-TS Voting Machine. Computer Science,
Princetone University. New Jersey : s.n., 2006.
72. Fischer, Eric A. Elections Reforms and Electronic Voting
Systems (DREs) : Analysis of Security Issues. Congressional Research and
Services, United States Congress. Washington DC : Congressional Research
and Services, 2003. CRS Report for Congress. November 2003.
73. Jones, Douglas W. Misassessment of Security in Computer-Based
Election Systems. 2, s.l. : RSA Laboratories, 2004, Vol. 7.
74. Genest, Christian and MacKay, Jock.
The Joy of Copulas : Bivariate Distributions with Uniform Copulas. The American Statistician. 1986, Vol.
40, 4, pp. 280 - 283.
75. Zheng, Ming and Klein, John P.
Estimates of Marginal Survival for Dependent Competing Risks Based on an
Assumed Copula. Biometrika. March
1995, Vol. 82, 1, pp. 127 - 138.
76. Whitt, Ward. Bivariate Distributions
with Given Marginals. The Annals of
Statistics. 1976, Vol. 4, 6, pp. 1280 - 1289.
77. Thomas, Kenneth R. Executive Branch Power to Postpone
Elections. Legislative Attorney, American Law Division, United States
Congress. Washington DC : Congressional Report Service, 2004. p. 9. By
Legislative Athorney, American Law Division. RL32471.
78. Tawn, Jonathan A. Modelling
Multivariate Extreme Value Distribution. Biometrika.
1990, Vol. 77, 2, pp. 245 - 253.
79. Spall, James C. Introduction to Stochastic Search and
Optimization. s.l. : Wiley & Sons, 2003. 0471330523.
80. Simon, Gary. Multivariate
Generalization of Kendall's Tau with Application to Data Reduction. 358,
s.l. : American Statistical Association, 1977, Journal of American
Statistical Association, Vol. 72, pp. 367 - 376.
81. Segall, Adrian. Stochastic Preocesses
in Estimation Theory. IEEE Transactions
on Information Theory. May 1976, Vols. IT-22, 3, pp. 275 - 286.
82. Schweizer, B. and Wolff, E. F. On
Nonparametric Measures of Dependence for Random Variables. The Annals of Statistics. July 1981,
Vol. 9, 4, pp. 879 - 885.
83. Schechter, Stuart E. Towards Econometric Models of the Security
Risk from Remote Attacks. s.l. : IEEE Computer Society, 2005, IEEE
Security & Privacy, pp. 40 -45. 1540-7993/05.
84. Scarsini, Marco and Venetoulias, Achilles. Bivariate Distributions with Nonmonotone
Dependence Structure. 421, s.l. : Ameican Statistical Association,
March 1993, Journal of the American Statistical Association, Vol. 88, pp. 338 -
344.
85. SAIC. Risk Assessment Report. Diebold AccuVote-TS Voting System and
Processes. Annapolis : Science Applications International
Corporation, September2, 2003. Department of Budget and Management Risk
Assement Report. SAIC-6099-2003-261.
86. Sacetta, Alessio. Copula Based Monte Carlo Integration in
Financial Problems. s.l. : CWPE, 2005.
87. Romano, Claudio. Applying Copula Function to Risk Management.
s.l. : Banca Roma, 2002. PhD Thesis.
88. Nelsen, Roger B. Copulas,
Characterization, Correlation, and Counterexamples. Mathematics Magazine. 1995, Vol. 68, 3, pp. 193 -198.
89. Mukhopadhyay, Arunabha, et al. e-Risk Management with Insurance: A
framework using copula aided Bayesian Belief Network. Hawaii : IEEE
Computer Society, 2006. Proceedings of the 39th Hawaii International Conference
on System Sciences. 0-7695-2507-5/06.
90. Molife, Rhashed. Using Copulas as a Measure of Dependence
Between Competing Cases of Mortality. Faculty of Actuarial Science and
Statistics, Sir John Cass Business School, City University of London. 2003.
Master Thesis .
91. Melchiori, Mario R. Which Archimedean Copula is the right one? s.l. :
Yield Curve E journal, 2003.
92. Melchiori, Mario R. Tools for Sampling Multivariate Archimedean
Copulas. s.l. : Yield Curve E-Journal, 2006.
93. Melanie Moses, Dave Didich, Richard Dean.
Systems Security for Wireless Systems
and Network. s.l. : National Security Agency, 1996.
CTIA/IMSEF/97.07.03.
94. Meester, Steven G. and MacKay, Jock. A
Parametric Model for Cluster Correlated Categorical Data. Biometrics. 1994, Vol. 50, 4, pp. 954
- 963.
95. McNeil, Alexander J., Frey, Rudiger and
Embrechts, Paul. Quantitative
Risk Management : Concepts , Techniques and Tools. s.l. : Princton
University Press, 2005.
96. McNeil, Alexander J. and Wendin, Jonathan.
Bayesian Inference for Generalized Linear Mixed Models for Portfolio Risk. Jounal of Emperical Finance. October
5, 2005. Submitted Article : No Information about actual publication.
97. Marshall, Albert W. and Olkin, Ingram.
Families of Multivariate Distributions. Journal
of the American Statistical Association. September 1988, Vol. 83, 403,
pp. 834 - 841.
98. Leite da Silva, A. M., et al. Dynamic Security Risk Assessment. s.l. :
IEEE, 1999, p. 7. 0-7803-5569-5/99.
99. Koyluogu, Ugur H. and Hickman, Andrew.
A Generalized Framework for Credit
Risk Portfolio Models. 1998.
100. Klaassen, Chris A.J. and Wellner, Jon A.
Efficient Estimation in the Bivariate Normal Copula Model: Normal Margins are
Least favorable. Bernoulli. March
1997, Vol. 3, 1, pp. 55 - 77.
101. Ken Lin, Gary Deamer. caBIG Security
Technology Evaluation. [ed.] Ken Lin and Gary Deamer. s.l., USA : Booz
Allen Hamilton, January 23, 2006. p. 114.
102. Joro, Tarja, Na, Paul and Niu, Anne R. A Simmulation-Based First-To-Default(FTD)
Credit Default Swap(CDS) Pricing Approach Under Jump-Diffusion. 2004.
Proceedings of the 2004 Winter Simulation Conference.
103. Joe, Harry. Multivariate Extreme-Value
Distributions with Applications to Environmental Data. The Canadian Journal of Statistics/La Revue Canadienne de Statistique. 1994,
Vol. 22, 1, pp. 47 - 67.
104. Jaynes, Edward Thompson. Probability
Theory - The Logic of Science. 1995.
105. Helder Parra Palaro, Luiz Koodi Hotta. Using
Conditional Copula to Estimate Value at Risk. 2006, Journal of Data
Science, pp. 93-115.
106. Genest, Christian and Rivest, Louis-Paul.
Statistical Inference Procedures for Bivariate Archimedean Copulas. Journal of the American Statistical
Association. September 1993, Vol. 88, 423, pp. 1034 - 1043.
107. GAO, United States General Accounting Office.
Information Security Management :
Learning from Leading Organizations. Accounting and Information
Division, United States General Accounting Office. Washington DC : GAO,
May 1998. p. 68, Executive Guide. GAO/AIMD-98-68.
108. Frederick Chong,
Dwayne Taylor. Federated Identity: Scenarios, Architecture, and
Implementation. http://msdn.microsoft.com/architecture.
[Online] 1, June 1, 2006. [Cited: June 28, 2006.]
http://msdn.microsoft.com/architecture/default.aspx?pull=/library/en-us/dnbda/html/federated.asp.
109. Dorofee, Audrey. Managing Information Security Risks Accross
the Enterprise. Software Engineering Institute, Carnagie Mellon
University. Pittsburgh : Carnagie Mellon University, 2002. p. 60.
110. Daas, Sarat C, Zhu, Yongfang and Jain, Anil
K. Validating a Biometric Authentication System: Sample Size
Requirements. IEEE Transactions on
Pattern Analysis and Machine Intelligence. 2006, Vol. 28, 12.
111. Cwik, J., et al. Conceptual and Statistical problems of
sister dependence. 3, s.l. : Biometrika Trust, Dec 1982,
Biometrika, Vol. 69, pp. 513 - 520.
112. Coles, Stuart. A sufficiency Property
Arising from the Characterization of Extremes of Markov Chains. Bernoulli. 200, Vol. 6, 1, pp. 183 -
190.
113. Carty, Lea V. Moody's Rating Migration and Credit Quality Correltion, 1920-1996. s.l. :
Moody's Investors Services, July 1997. p. 25, Global Credit Research : Special
Comment.
114. Brunel, Nicolas, Pieczynski, Wojeciech and
Derrode, Stephane. Copulas in Vectorial Hidden Markov Chains for
Multicomponent Image Segmentation. 2005, pp. II-718 - II-720.
115. Brown, Peter E., et al. The Mathematics of Statistical Machine
Translation: Parameter Estimation. 2, s.l. : Association for
Computational Linguistics, 1993, Vol. 19.
116. Bretthorst, Larry G. Bayesian Spectrum Analysis and Parameter
Estimation. s.l. : Springer-Verlag, 1988. A web pdf version made
available by the author after original ran out of print.
117. Ballerini, Rocco. Archimedean Copulas,
Exchangeability, and Max-Stability. Journal
of Applied Probability. June 1994, Vol. 31, 2, pp. 383-390.
118. Aas, Kjersti. Modelling the dependence structure of financial assets: A Survey of
four Copulas. s.l. : Norwegian Computing Center, 2005.
119. Marshall, Albert W. and Olkin, Ingram.
A New Method for Adding a Parameter to a Family of Distributions with
Application to the Exponential Weibull Families. Biometrika. September 1997, Vol. 84, 3, pp. 641 - 652.
120. Alsina, Claudi, Frank, Maurice J and Schweizer,
Berthold. Associative
Functions, Triangular Norms and Copulas. Singapore : World
Scientific Publishing Co, 2006. 981-256-67-6.
121. Dall'Aglio, G, Kotz, S and Salinetti, G.
Advances in Probability Distributions
with Given Marginals. [ed.] Hazewinkel M. Dordrecht : Kluwer
Academic Publishers, 1991. Vol. 67. 0-7923-1156-6.
122. Nelson, Roger B. An Introduction to Copulas. s.l. :
Springer Science+Business Media, Inc, 2006. 0-387-28659-4.
123. Delfs, Hans and Knebl, Helmut. Introduction to Cryptography, Principles and
Applications. Heidelberg : Spinger-Verlag, 2002. 3-540-42278-1.
124. Schneier, Bruce. Applied Cryptography. s.l. :
John Wiley & Sons, Inc., 1996. 0-471-11709-9.
125. Australian Capital Territory Electoral
Commission. ACT Electoral Commission - Electronic Voting. [Online] ACT
Electoral Commission, 2004. [Cited: December 20, 2004.]
http://www.elections.act.gov.au/pubs.html.
126. Rice, R. E., Schweizer, B. and Sklar, A.
When is f(z) = az^2 + bz + c ? The
American Mathematical Monthly. April 1980, Vol. 87, 4, pp. 252 - 263.
127. Quesada-Molina, Jose Juan, Rodriquez-Lallena,
Jose Antonio and Ubeda-Flores, Manuel. What are copulas. s.l. : Garcia de Galdeano, 2003,
Monografias del Semin, Vol. 27, pp. 499-506.
128. Alsina, C and Quesada, J J. Of the Associativity of C(x,y) and x-C(x,
1-y). s.l. : IEEE, 1988, IEEE Transaction of Fuzzy Logic.
0195-623X/88.
129. Brunel, N and Pieczynski, W. Unsupervised Signal Restoration Using
Copulas and Pairwise Markov Chains. St. Louis : IEEE, 2003.
Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing. pp. 102
- 105. 0-7803-7997-7/03.
130. Cherubini, Umberto, Luciano, Elisa and
Vecchiato, Walter. Copula
Methods in Finance. s.l. : John Wiley & Sons, 2004. p. 310.
978-0-470-86344-2.
131. Duda, Richard O, Hart, Peter E and Stork,
David G. Pattern
Classification. s.l. : John Wiley & Sons, 2001.
132. Frees, Edward W. and Valdez, Emiliano A. Understanding Relationships Using Copulas.
1, s.l. : Society of Actuaries, 1999, North America Actuarial Journal, Vol.
2, pp. 1-25.
133. Maybeck, Peter S. Stochastic Models, Estimation and Control. s.l. :
Academic Press, 1979. Vol. 1.
134. McNeil, Alexander J and Demarta, Stefano.
The t Copula and Related Concepts. 1,
s.l. Blackwell Publishing, 2004, International Statistical Review Vol.
73.
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