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Livros sobre o tema "Inference"

Autor: Grafiati

Publicado: 4 de junho de 2021

Última modificação: 1 de agosto de 2024

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1

Bazett, Trefor. Bayesian Inference. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95792-6.

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2

Wieczorek, Wojciech. Grammatical Inference. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46801-3.

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3

Schölkopf, Bernhard, Zhiyuan Luo e Vladimir Vovk, eds. Empirical Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41136-6.

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4

Bromek, Tadeusz, e Elżbieta Pleszczyńska, eds. Statistical Inference. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0575-7.

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5

Harney, Hanns Ludwig. Bayesian Inference. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41644-1.

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6

Panik, Michael J. Statistical Inference. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118309773.

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7

Honavar, Vasant, e Giora Slutzki, eds. Grammatical Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0054058.

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8

Pouly, Marc, e Jürg Kohlas. Generic Inference. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118010877.

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9

Harney, Hanns L. Bayesian Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-06006-3.

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10

Verbelen, Tim, Pablo Lanillos, Christopher L. Buckley e Cedric De Boom, eds. Active Inference. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64919-7.

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11

1963-, Polson Nicholas G., e Tiao George C. 1933-, eds. Bayesian inference. Aldershot, Hants, England: E. Elgar Pub. Co., 1995.

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12

L, Berger Roger, ed. Statistical inference. Pacific Grove, Calif: Brooks/Cole Pub. Co., 1990.

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13

Tan, W. Y., e N. Balakrishnan, eds. Robust inference. New York, USA: M. Dekker, 1986.

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14

Silvey, S. D. Statistical inference. London: Chapman and Hall, 1988.

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15

Lee, Won Don. Probabilistic inference. Urbana, Ill: Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1986.

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16

Garthwaite, Paul H. Statistical inference. London: Prentice Hall, 1995.

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17

Garthwaite, Paul H. Statistical inference. 2^a ed. Oxford: Oxford University Press, 2002.

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18

Oakes, Michael W. Statistical inference. Chestnut Hill, MA: Epidemiology Resources Inc., 1990.

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19

Harold, Jeffreys. Scientific inference. Cambridge: Cambridge University Press, 2007.

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20

Buckley, Christopher L., Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Noor Sajid, Hideaki Shimazaki, Tim Verbelen e Martijn Wisse, eds. Active Inference. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47958-8.

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21

Buckley, Christopher L., Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Noor Sajid, Hideaki Shimazaki e Tim Verbelen, eds. Active Inference. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28719-0.

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22

J, Rothman Kenneth, Lanes Stephan F e Society for Epidemiologic Research (U.S.). Meeting, eds. Causal inference. Chestnut Hill, MA: Epidemiology Resources, 1988.

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23

L, Berger Roger, ed. Statistical Inference. 2^a ed. Australia: Thomson Learning, 2002.

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24

S, Maddala G., e Rao C. R, eds. Robust inference. Amsterdam: Elsevier, 1997.

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25

T, Jolliffe I., e Jones Byron 1951-, eds. Statistical inference. Oxford: Oxford University Press, 2002.

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26

Dridi, Ramdan. Semiparametric indirect inference. Bristol: University of Bristol, Department of Economics, 1999.

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27

Dolan, John M. Inference and imagination. Minneapolis, MN: Archimedean Point Press, 1994.

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28

Deshmukh, Shailaja, e Madhuri Kulkarni. Asymptotic Statistical Inference. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9003-0.

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29

Sainsbury, Mark. Inference. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198803348.003.0006.

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Display theory predicts that no inferential relations among attitude attributions are based on the logical or semantic properties of the expressions in attribution complements. This chapter shows various ways in which there may be an illusion that such relations obtain. One common basis for the illusion is that we implicitly appeal to psychological facts. Since there is no reason to think these are necessary, the inferences are not truth preserving of necessity, even if they generally have true conclusions when they have true premises. They are examples of “plausible reasoning”. Wanting and fearing are discussed in detail as potential sources of the apparently inferential phenomena.

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30

INFERENCE. [Place of publication not identified]: RINGWOOD Publishing, 2019.

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31

Mukhyopadhyay, Pritam. Inference. Independently Published, 2019.

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32

Patel, Shantilal R. Statistical Inference: Classical and Bayesian Inference. I.K. International Publishing House Pvt. Ltd, 2022.

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33

Silvey, S. D. Statistical Inference. CRC Press LLC, 2017.

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34

Pouly, Marc, e Juerg Kohlas. Generic Inference. Wiley & Sons, Incorporated, John, 2011.

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35

Ackermann, Robert. Nondeductive Inference. Taylor & Francis Group, 2019.

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36

Panik, Michael J. Statistical Inference. Wiley & Sons, Incorporated, John, 2012.

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37

Teng, Choh Man, e Kyburg Henry E. Jr. Uncertain Inference. Cambridge University Press, 2009.

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38

Gelman, Andrew, e Deborah Nolan. Statistical inference. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.003.0009.

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This chapter begins with a very successful demonstration that illustrates many of the general principles of statistical inference, including estimation, bias, and the concept of the sampling distribution. Students each take a “random” sample of different size candies, weigh them, and estimate the total weight of all candies. Then various demonstrations and examples are presented that take the students on the transition from probability to hypothesis testing, confidence intervals, and more advanced concepts such as statistical power and multiple comparisons. These activities include use an inflatable globe, short-term memory test, first digits of street addresses, and simulated student IQs.

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39

Govindarajulu, Z. Nonparametric Inference. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/6244.

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40

Golan, Amos. Rational Inference. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.003.0002.

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In this chapter I present arguments for the use of info-metrics as a fundamental framework for rational inference. The chapter consists of two interdependent parts. In the first I provide the framework for rational inference, which involves the use of a specific decision function to achieve the desired inference. In the second part I summarize four sets of axioms to justify the decision function argued for in the first part. All axioms lead to the same decision function: the entropy function of Boltzmann, Gibbs, and Shannon. In this chapter I emphasize underdetermined problems and problems of insufficient information, but I also discuss inference based on information resulting from repeated independent experiments. The same entropy function is identified in each case, as well as the desired decision function.

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41

Ackermann, Robert. Nondeductive Inference. Routledge, 2019. http://dx.doi.org/10.4324/9780367853907.

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42

Cunningham, Scott. Causal Inference. Yale University Press, 2021. http://dx.doi.org/10.12987/9780300255881.

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43

Bayesian Inference. Elsevier, 2010. http://dx.doi.org/10.1016/c2009-0-01674-2.

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44

Josephson, John R., e Susan G. Josephson, eds. Abductive Inference. Cambridge University Press, 1994. http://dx.doi.org/10.1017/cbo9780511530128.

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45

King, Gary, Ori Rosen e Martin A. Tanner, eds. Ecological Inference. Cambridge University Press, 2004. http://dx.doi.org/10.1017/cbo9780511510595.

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46

Predictive Inference. Routledge, 2017. http://dx.doi.org/10.1201/9780203742310.

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47

Griffiths, Thomas L., Joshua B. Tenenbaum e Charles Kemp. Bayesian Inference. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199734689.013.0003.

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48

Migon, Helio S., Dani Gamerman e Francisco Louzada. Statistical Inference. Chapman and Hall/CRC, 2014. http://dx.doi.org/10.1201/b17229.

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49

Tejedor, Javier Prieto, ed. Bayesian Inference. InTech, 2017. http://dx.doi.org/10.5772/66264.

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50

Azzalini. Statistical Inference. Kluwer Academic Publishers Group, 1995.

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