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1

Samson, Danny. Decision analysis models of futures options purchase decisions. Melbourne: University of Melbourne. Graduate School of Management, 1990.

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2

Bucciarelli, Edgardo, Shu-Heng Chen, and Juan Manuel Corchado, eds. Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99698-1.

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3

Gruber, Josef, ed. Econometric Decision Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-51675-7.

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4

Olson, David Louis. Decision support models. Dubuque, Iowa: Kendall/Hunt, 1988.

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5

1952-, Ben-Haim Yakov, ed. Info-gap decision theory: Decisions under severe uncertainty. 2nd ed. Oxford: Academic, 2006.

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6

Bouyssou, Denis, Thierry Marchant, Marc Pirlot, Patrice Perny, Alexis Tsoukiàs, and Philippe Vincke. Evaluation and Decision Models. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-1593-7.

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7

Kumar, G. Surya. Decision making & math models. Arlington, MA: Consortium for Mathematics and Its Applications, 1989.

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8

Leeflang, Peter S. H., Dick R. Wittink, Michel Wedel, and Philippe A. Naert. Building Models for Marketing Decisions. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4050-2.

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9

Kuik, Roelof. Batching decisions: Structure and models. Fontainebleau: INSEAD, 1993.

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10

Myerson, Roger B. Probability models for economic decisions. Belmont, CA: Thomson/Brooke/Cole, 2005.

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11

Leeflang, P. S. H., 1946-, ed. Building models for marketing decisions. Boston: Kluwer, 2000.

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12

J, Willis Robert. Computer models for business decisions. Chichester [West Sussex]: Wiley, 1987.

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13

Wierenga, Berend, ed. Handbook of Marketing Decision Models. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78213-3.

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14

Mitra, Gautam, Harvey J. Greenberg, Freerk A. Lootsma, Marcel J. Rijkaert, and Hans J. Zimmermann, eds. Mathematical Models for Decision Support. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83555-1.

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15

Wierenga, Berend, and Ralf van der Lans, eds. Handbook of Marketing Decision Models. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56941-3.

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16

Murty, Katta G., ed. Models for Optimum Decision Making. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40212-9.

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17

NATO Advanced Study Institute on Mathematical Models for Decision Support (1988 Val d'Isère, France). Mathematical models for decision support. Edited by Mitra Gautam, Greenberg Harvey J, and North Atlantic Treaty Organization. Scientific Affairs Division. Berlin: Springer-Verlag, 1988.

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18

Kumar, G. Surya. Decision making and math models. Arlington, Mass: Consortium for Mathematics and Its Applications, Inc. (COMAP), 1989.

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19

Mitra, Gautam. Mathematical Models for Decision Support. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988.

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20

Klugman, Stuart A. Loss models: From data to decisions. 3rd ed. Hoboken, N.J: John Wiley & Sons, 2008.

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21

H, Panjer Harry, and Willmot Gordon E. 1957-, eds. Loss models: From data to decisions. 4th ed. Hoboken, N.J: Wiley, 2012.

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22

H, Panjer Harry, and Willmot Gordon E. 1957-, eds. Loss models: From data to decisions. 2nd ed. Hoboken, N.J: Wiley Interscience, 2004.

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23

Klugman, Stuart A. Loss Models: From Data to Decisions. 3rd ed. Hoboken: John Wiley & Sons, 2012.

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24

H, Panjer Harry, and Willmot Gordon E. 1957-, eds. Loss models: From data to decisions. New York: Wiley, 1998.

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25

Pötter, Ulrich. Models for interdependent decisions over time. Colchester: European Science Foundation, Scientific Network on Household Panel Studies, University of Essex, 1992.

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26

Olson, David Louis. Decision support models and expert systems. Houston TX: Dame Publications, 1997.

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27

Guarnieri, Patricia, ed. Decision Models in Engineering and Management. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11949-6.

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28

1944-, Courtney James F., ed. Decision support models and expert systems. New York: Macmillan, 1992.

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29

Busemeyer, Jerome R. Quantum models of cognition and decision. Cambridge: Cambridge University Press, 2012.

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30

Nonlinear models for economic decision processes. London: Imperial College Press, 2010.

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31

Rob, Ranyard, Crozier W. Ray 1945-, and Svenson Ola, eds. Decision making: Cognitive models and explanations. London: Routledge, 1997.

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32

New York (State). Engineering Research and Development Bureau and United States. Federal Highway Administration, eds. Decision models for winter highway maintenance. Albany, N.Y: Engineering Research and Development Bureau, New York State Dept. of Transportation, 1989.

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33

Models in environmental regulatory decision making. Washington, D.C: National Academies Press, 2007.

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34

Busemeyer, Jerome R. Quantum models of cognition and decision. Cambridge: Cambridge University Press, 2012.

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35

Ashby, F. Gregory, and Fabian A. Soto. Multidimensional Signal Detection Theory. Edited by Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.013.2.

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Abstract:
Multidimensional signal detection theory is a multivariate extension of signal detection theory that makes two fundamental assumptions, namely that every mental state is noisy and that every action requires a decision. The most widely studied version is known as general recognition theory (GRT). General recognition theory assumes that the percept on each trial can be modeled as a random sample from a multivariate probability distribution defined over the perceptual space. Decision bounds divide this space into regions that are each associated with a response alternative. General recognition theory rigorously defines and tests a number of important perceptual and cognitive conditions, including perceptual and decisional separability and perceptual independence. General recognition theory has been used to analyze data from identification experiments in two ways: (1) fitting and comparing models that make different assumptions about perceptual and decisional processing, and (2) testing assumptions by computing summary statistics and checking whether these satisfy certain conditions. Much has been learned recently about the neural networks that mediate the perceptual and decisional processing modeled by GRT, and this knowledge can be used to improve the design of experiments where a GRT analysis is anticipated.
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36

HELLER. Decisions d'Investisse Par Models Option: Les Decisions d'Investissement Par Modeles Optionnels. ISTE Editions Ltd., 2019.

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37

Chen, Shu-Heng, Juan Manuel Corchado, and Edgardo Bucciarelli. Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions. Springer, 2018.

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38

RAGSDALE. Decision Support Models. Pearson Education, Limited, 2004.

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39

Kapoor. Computer Aided Decision Models. McGraw-Hill Education, 1989.

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40

Weirich, Paul. Models of Decision-Making. Cambridge University Press, 2015.

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41

Bouyssou, Denis, Thierry Marchant, and Marc Pirlot. Evaluation and Decision Models. Springer, 2012.

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42

Zambrano, Eduardo, and Roger B. Myerson. Probability Models for Economic Decisions. MIT Press, 2019.

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43

Wittink, Dick R., Peter S. H. Leeflang, Philippe A. Naert, and Michel Wedel. Building Models for Marketing Decisions. Springer London, Limited, 2013.

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44

Probability Models for Economic Decisions. MIT Press, 2019.

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45

Wittink, Dick R., Peter S. H. Leeflang, and Michel Wedel. Building Models for Marketing Decisions. Springer, 2014.

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46

Rossi, Guido Antonio. Changing Models. Torino [Italy] : Levrotto & Bella, 2005.

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47

von Halle, Barbara, and Larry Goldberg. The Decision Model. Auerbach Publications, 2009. http://dx.doi.org/10.1201/9781420082821.

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48

Wierenga, Berend, and Ralf van der Lans. Handbook of Marketing Decision Models. Springer, 2017.

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49

Wierenga, Berend. Handbook of Marketing Decision Models. Springer, 2010.

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50

Wierenga, Berend, and Ralf van der Lans. Handbook of Marketing Decision Models. Springer, 2018.

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