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Journal articles on the topic 'Probabilities'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Mugur-Sch�chter, Mioara. "Quantum probabilities, Kolmogorov probabilities, and informational probabilities." International Journal of Theoretical Physics 33, no. 1 (1994): 53–90. http://dx.doi.org/10.1007/bf00671614.

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2

Yukalov, Vyacheslav, and Didier Sornette. "Quantum Probabilities as Behavioral Probabilities." Entropy 19, no. 3 (2017): 112. http://dx.doi.org/10.3390/e19030112.

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3

Czeiszperger, Michael, and Stephen Jeske. "Probabilities." Computer Music Journal 14, no. 2 (1990): 68. http://dx.doi.org/10.2307/3679716.

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4

Fang, Di, Jenny Chong, and Jeffrey R. Wilson. "Predicted Probabilities' Relationship to Inclusion Probabilities." American Journal of Public Health 105, no. 5 (2015): 837–39. http://dx.doi.org/10.2105/ajph.2015.302592.

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5

Hájek, Alan. "Probabilities of counterfactuals and counterfactual probabilities." Journal of Applied Logic 12, no. 3 (2014): 235–51. http://dx.doi.org/10.1016/j.jal.2013.11.001.

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6

Lewis, David. "Probabilities of Conditionals and Conditional Probabilities II." Philosophical Review 95, no. 4 (1986): 581. http://dx.doi.org/10.2307/2185051.

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7

Barmpalias, George, and Andrew Lewis-Pye. "Computing halting probabilities from other halting probabilities." Theoretical Computer Science 660 (January 2017): 16–22. http://dx.doi.org/10.1016/j.tcs.2016.11.013.

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8

Fréché, Jean-Pierre. "Des probabilités négatives ?" Revue des questions scientifiques 193, no. 1-2 (2022): 49–68. http://dx.doi.org/10.14428/qs.v193i1-2.70203.

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Jusqu’en 1932, les probabilités, tant en mathématique qu’en physique, étaient positives. Mais cette année-là, Wigner publia un article qui introduisait en physique statistique quantique une distribution de probabilités prenant aussi bien des valeurs négatives que des valeurs positives. Le texte qui suit établit d’abord brièvement un parallèle entre l’avènement des nombres négatifs et des nombres complexes au XVIe siècle d’une part, et l’avènement des probabilités négatives au XXe siècle d’autre part. Puis il décrit un « dispositif de pensée » qui propose des probabilités positives et négatives

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9

Grunwald, P. D., and J. Y. Halpern. "Updating Probabilities." Journal of Artificial Intelligence Research 19 (October 1, 2003): 243–78. http://dx.doi.org/10.1613/jair.1164.

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As examples such as the Monty Hall puzzle show, applying conditioning to update a probability distribution on a ``naive space'', which does not take into account the protocol used, can often lead to counterintuitive results. Here we examine why. A criterion known as CAR (``coarsening at random'') in the statistical literature characterizes when ``naive'' conditioning in a naive space works. We show that the CAR condition holds rather infrequently, and we provide a procedural characterization of it, by giving a randomized algorithm that generates all and only distributions for which CAR holds.

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10

Warrington, Gregory S. "Juggling Probabilities." American Mathematical Monthly 112, no. 2 (2005): 105. http://dx.doi.org/10.2307/30037409.

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11

McVey, Jack L., Anthony Kettaneh, Tibor R. Machan, John Bryant, and Alfred R. Beronio. "Future Probabilities." Science News 135, no. 9 (1989): 131. http://dx.doi.org/10.2307/3973594.

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12

Jeffrey, Richard. "Unknown probabilities." Erkenntnis 45, no. 2-3 (1996): 327–35. http://dx.doi.org/10.1007/bf00276797.

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13

Pruss, A. R. "Conditional probabilities." Analysis 72, no. 3 (2012): 488–91. http://dx.doi.org/10.1093/analys/ans076.

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14

Hansson, Sven Ove. "Past Probabilities." Notre Dame Journal of Formal Logic 51, no. 2 (2010): 207–23. http://dx.doi.org/10.1215/00294527-2010-013.

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15

Dassios, Angelos. "Ruin Probabilities." Journal of the American Statistical Association 97, no. 460 (2002): 1211–12. http://dx.doi.org/10.1198/jasa.2002.s243.

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16

Fletcher, J. "Conditional probabilities." BMJ 338, jan14 3 (2009): b113. http://dx.doi.org/10.1136/bmj.b113.

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17

Benci, Vieri, Leon Horsten, and Sylvia Wenmackers. "Infinitesimal Probabilities." British Journal for the Philosophy of Science 69, no. 2 (2018): 509–52. http://dx.doi.org/10.1093/bjps/axw013.

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18

Litwiller, Bonnie H., and David R. Duncan. "Keno Probabilities." School Science and Mathematics 87, no. 1 (1987): 33–39. http://dx.doi.org/10.1111/j.1949-8594.1987.tb17216.x.

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19

Warrington, Gregory S. "Juggling Probabilities." American Mathematical Monthly 112, no. 2 (2005): 105–18. http://dx.doi.org/10.1080/00029890.2005.11920175.

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20

Roon, Hannah. "Statistical probabilities." Pigment & Resin Technology 16, no. 6 (1987): 4. http://dx.doi.org/10.1108/eb042366.

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21

Hartigan, J. A., and T. B. Murphy. "Inferred probabilities." Journal of Statistical Planning and Inference 105, no. 1 (2002): 23–34. http://dx.doi.org/10.1016/s0378-3758(01)00202-6.

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22

DE COOMAN, GERT. "Imprecise probabilities." Risk Decision and Policy 5, no. 2 (2000): 107–9. http://dx.doi.org/10.1017/s135753090000017x.

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23

Jonah, Charles D. "Cheating Probabilities." Journal of Chemical Education 75, no. 9 (1998): 1089. http://dx.doi.org/10.1021/ed075p1089.3.

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24

George, Glyn. "Parallel probabilities." Mathematical Gazette 104, no. 560 (2020): 271–80. http://dx.doi.org/10.1017/mag.2020.50.

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After several years of teaching an introduction to probability and statistics for engineering degree students, my attention has been captured by some variations on the familiar general addition law of probability. Network analysis of components connected in parallel is one of many applications.

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25

Milne, Peter. "Physical probabilities." Synthese 73, no. 2 (1987): 329–59. http://dx.doi.org/10.1007/bf00484746.

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26

Maas, Kees, Marco Steenbergen, and Willem Saris. "Vote probabilities." Electoral Studies 9, no. 2 (1990): 91–107. http://dx.doi.org/10.1016/0261-3794(90)90002-p.

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27

Skilling, John. "Prior probabilities." Synthese 63, no. 1 (1985): 1–34. http://dx.doi.org/10.1007/bf00485953.

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28

Drossos, C. A., and P. L. Theodoropoulos. "-fuzzy probabilities." Fuzzy Sets and Systems 78, no. 3 (1996): 355–69. http://dx.doi.org/10.1016/0165-0114(96)84617-3.

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29

Uzhga-Rebrov, O. "UNCERTAIN PROBABILITIES." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (June 26, 2006): 377. http://dx.doi.org/10.17770/etr2003vol1.2020.

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The uncertainty of probabilistic evaluations results from the lack of sufficient information and/or knowledge underlying those random events. Uncertainty representation in the form of second order probability distribution or interval evaluations does not cause any objections from the theoretical point of view. On the other hand, what is worthy in the second order probabilities is that they allow one to model a real uncertainty of subjective probabilistic evaluations resulting from the lack of information and/or knowledge. Processing of uncertain information regarding probabilistic evaluations

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30

Pharoah, P. D. P. "Balancing probabilities." BMJ 342, may17 2 (2011): d3048. http://dx.doi.org/10.1136/bmj.d3048.

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31

Dubucs, J. "Embedded probabilities." Theory and Decision 30, no. 3 (1991): 279–84. http://dx.doi.org/10.1007/bf00132448.

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32

Viscusi, W. Kip, and William N. Evans. "Behavioral Probabilities." Journal of Risk and Uncertainty 32, no. 1 (2006): 5–15. http://dx.doi.org/10.1007/s10797-006-6663-6.

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33

Easton, Kristen L. "Distinct Probabilities." Rehabilitation Nursing 19, no. 5 (1994): 303–4. http://dx.doi.org/10.1002/j.2048-7940.1994.tb00828.x.

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34

Gorski, Andrew. "Chi-Square Probabilities are Poisson Probabilities in Disguise." IEEE Transactions on Reliability R-34, no. 3 (1985): 209–11. http://dx.doi.org/10.1109/tr.1985.5222117.

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35

Khrennikov, Andrei. "CHSH Inequality: Quantum Probabilities as Classical Conditional Probabilities." Foundations of Physics 45, no. 7 (2014): 711–25. http://dx.doi.org/10.1007/s10701-014-9851-8.

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36

Li, Xiaoou, and Jingchen Liu. "Rare-event simulation and efficient discretization for the supremum of Gaussian random fields." Advances in Applied Probability 47, no. 3 (2015): 787–816. http://dx.doi.org/10.1239/aap/1444308882.

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In this paper we consider a classic problem concerning the high excursion probabilities of a Gaussian random fieldfliving on a compact setT. We develop efficient computational methods for the tail probabilitiesℙ{supTf(t) >b}. For each positive ε, we present Monte Carlo algorithms that run inconstanttime and compute the probabilities with relative error ε for arbitrarily largeb. The efficiency results are applicable to a large class of Hölder continuous Gaussian random fields. Besides computations, the change of measure and its analysis techniques have several theoretical and practical indic

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37

Li, Xiaoou, and Jingchen Liu. "Rare-event simulation and efficient discretization for the supremum of Gaussian random fields." Advances in Applied Probability 47, no. 03 (2015): 787–816. http://dx.doi.org/10.1017/s0001867800048837.

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In this paper we consider a classic problem concerning the high excursion probabilities of a Gaussian random fieldfliving on a compact setT. We develop efficient computational methods for the tail probabilitiesℙ{supTf(t) &gt;b}. For each positive ε, we present Monte Carlo algorithms that run inconstanttime and compute the probabilities with relative error ε for arbitrarily largeb. The efficiency results are applicable to a large class of Hölder continuous Gaussian random fields. Besides computations, the change of measure and its analysis techniques have several theoretical and practical i

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38

Dhami, Mandeep K., and Thomas S. Wallsten. "Interpersonal comparison of subjective probabilities: Toward translating linguistic probabilities." Memory & Cognition 33, no. 6 (2005): 1057–68. http://dx.doi.org/10.3758/bf03193213.

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39

Rédel, Miklós. "Quantum conditional probabilities are not probabilities of quantum conditional." Physics Letters A 139, no. 7 (1989): 287–90. http://dx.doi.org/10.1016/0375-9601(89)90454-4.

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40

Suppes, Patrick, and Mario Zanotti. "Conditions on upper and lower probabilities to imply probabilities." Erkenntnis 31, no. 2-3 (1989): 323–45. http://dx.doi.org/10.1007/bf01236568.

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41

Syukur, Andi Abd khaliq, Aquarini Priyatna, and Lina Meilinawati Rahayu. "KEMATIAN DAN PERASAAN KEHILANGAN: KONSTRUKSI IDENTITAS QUEER DALAM EMPAT KARYA YOSHIMOTO (Death And Sense of Loss: Queer Identity Construction in Four Yoshimoto’s Works)." METASASTRA: Jurnal Penelitian Sastra 8, no. 2 (2016): 193. http://dx.doi.org/10.26610/metasastra.2015.v8i2.193-210.

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Empat novelet Yoshimoto, yaitu Kitchen (1988), Moonlight Shadow (1988), Hardboiled (2001), dan Hardluck (2001) menghadirkan kematian dan perasaan kehilangan di awal narasi. Kematian dan perasaan kehilangan membuka probabilitas baru sebagai bagian konstruksi identitas queer, seperti kematian sebagai pemutusan matrix heteroseksual, perasaan kehilangan sebagai perubahan identitas gender, penerimaan orang asing sebagai anggota keluarga, hubungan bersifat inses, homoseksualitas perempuan, transgenderisme, dan perubahan peran dalam anggota keluarga. Penelitian ini dilakukan untuk menganalisis cara k

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42

Marchildon, Louis. "À propos du lien entre la théorie quantique et les probabilités." Revue des questions scientifiques 192, no. 1-2 (2021): 93–115. http://dx.doi.org/10.14428/qs.v192i1-2.70013.

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La théorie des probabilités et la théorie quantique, l’une mathématique et l’autre physique, s’apparentent dans la mesure où chacune admet plusieurs interprétations fort différentes. Certains ont proposé que les problèmes conceptuels de la théorie quantique puissent être, sinon résolus, du moins atténués par une interprétation adéquate des probabilités. Nous montrerons plutôt, à travers un survol historique et analytique des probabilités et de la théorie quantique, que si certaines interprétations de l’une et de l’autre s’agencent particulièrement bien, aucune ne s’impose de façon unique.&#x0D

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43

Bartoszek, Wojciech. "On concentrated probabilities." Annales Polonici Mathematici 61, no. 1 (1995): 25–38. http://dx.doi.org/10.4064/ap-61-1-25-38.

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44

Papineau, David. "Probabilities and Causes." Journal of Philosophy 82, no. 2 (1985): 57. http://dx.doi.org/10.2307/2026555.

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45

Widen, Holly M., James B. Elsner, Rizalino B. Cruz, et al. "Adjusted Tornado Probabilities." E-Journal of Severe Storms Meteorology 8, no. 7 (2021): 1–12. http://dx.doi.org/10.55599/ejssm.v8i7.52.

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Tornado occurrence rates computed from the available reports are biased low relative to the unknown true rates. To correct for this low bias, the authors demonstrate a method to estimate the annual probability of being struck by a tornado that uses the average report density estimated as a function of distance from nearest city/town center. The method is demonstrated on Kansas and then applied to 15 other tornado-prone states from Nebraska to Tennessee. States are ranked according to their adjusted tornado rate and comparisons are made with raw rates published elsewhere. The adjusted rates, ex

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46

Page, Don N. "Possibilities for probabilities." Journal of Cosmology and Astroparticle Physics 2022, no. 10 (2022): 023. http://dx.doi.org/10.1088/1475-7516/2022/10/023.

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Abstract In ordinary situations involving a small part of the universe, Born's rule seems to work well for calculating probabilities of observations in quantum theory. However, there are a number of reasons for believing that it is not adequate for many cosmological purposes. Here a number of possible generalizations of Born's rule are discussed, explaining why they are consistent with the present statistical support for Born's rule in ordinary situations but can help solve various cosmological problems.

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47

Drees, Holger, and Laurens de Haan. "Estimating failure probabilities." Bernoulli 21, no. 2 (2015): 957–1001. http://dx.doi.org/10.3150/13-bej594.

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48

Fletcher, Mike. "CALCULATING DEPENDENT PROBABILITIES." Mathematics Enthusiast 6, no. 1-2 (2009): 91–94. http://dx.doi.org/10.54870/1551-3440.1137.

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49

Gottschalk, Lars. "Regional Exceedance Probabilities." Hydrology Research 20, no. 4-5 (1989): 201–14. http://dx.doi.org/10.2166/nh.1989.0016.

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Construction of a regional flood frequency curve is based, as a rule, on fitting this curve to representative quantiles. In a regional sample of floods the probability of extreme values corresponding to return periods, that exceed the record lengths, is much larger than that of individual series, used to determine the representative quantiles. The probabilities of exceedance of regional extremes can be calculated straightforward in case of independent data, applying the theory of order statistics. For regionally dependent data one can define an equivalent number of independent regional series

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50

Karni, Edi, and Zvi Safra. "Rank-Dependent Probabilities." Economic Journal 100, no. 401 (1990): 487. http://dx.doi.org/10.2307/2234135.

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