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Books on the topic 'Bayesian interpretation'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

B, Desai Uday, ed. Bayesian approach to image interpretation. Boston: Kluwer Academic Publishers, 2001.

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2

Natalie, Hicks Tacha, and Buckleton John S, eds. Forensic interpretation of glass evidence. Boca Raton: CRC Press, 2000.

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3

Bayesian methods in diagnostic medicine. Boca Raton: Taylor & Francis, 2007.

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4

Kopparapu, Sunil K., and Uday B. Desai. Bayesian Approach to Image Interpretation. Springer, 2013.

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5

Kopparapu, Sunil K., and Uday B. Desai. Bayesian Approach to Image Interpretation. Springer London, Limited, 2006.

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6

Bayesian Approach to Image Interpretation. Boston: Kluwer Academic Publishers, 2002. http://dx.doi.org/10.1007/b117231.

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7

Curran, James Michael, John S. Buckleton, and Tacha Natalie Hicks Champod. Forensic Interpretation of Glass Evidence. Taylor & Francis Group, 2000.

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8

(Editor), James Michael Curran, Tacha Natalie Hicks Champod (Editor), and John S. Buckleton (Editor), eds. Forensic Interpretation of Glass Evidence. CRC, 2000.

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9

Curran, James Michael, John S. Buckleton, and Tacha Natalie Hicks Champod. Forensic Interpretation of Glass Evidence. Taylor & Francis Group, 2000.

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10

Curran, James Michael. Forensic Interpretation of Glass Evidence. Taylor & Francis Group, 2010.

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11

Broemeling, Lyle D. Bayesian Biostatistics and Diagnostic Medicine. Chapman & Hall/CRC, 2007.

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12

Abdel-Fattah, Abdel-Fattah A. Accuracy of item response theory parameter estimates using maximum likelihood and Bayesian procedures as implemented in LOGIST and BILOG. 1990.

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13

Kopparapu, Sunil K., and Uday B. Desai. Bayesian Approach to Image Interpretation (The Kluwer International Series in Engineering and Computer Science, Volume 616) (The Springer International Series in Engineering and Computer Science). Springer, 2001.

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14

Kockelman, Paul. Algorithms, Agents, and Ontologies. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190636531.003.0007.

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This chapter details the inner workings of spam filters, algorithmic devices that separate desirable messages from undesirable messages. It argues that such filters are a particularly important kind of sieve insofar as they readily exhibit key features of sieving devices in general, and algorithmic sieving in particular. More broadly, it describes the relation between ontology (assumptions that drive interpretations) and inference (interpretations that alter assumptions) as it plays out in the classification and transformation of identities, types, or kinds. Focusing on the unstable processes whereby identifying algorithms, identified types, and evasive transformations are dynamically coupled over time, it also theorizes various kinds of ontological inertia and highlights various kinds of algorithmic ineffability. Finally, it shows how similar issues underlie a much wider range of processes, such as the Turing Test, Bayesian reasoning, and machine learning more generally.

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15

Rieth, Timothy, and Ethan E. Cochrane. The Chronology of Colonization in Remote Oceania. Edited by Ethan E. Cochrane and Terry L. Hunt. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199925070.013.010.

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Colonization of Remote Oceania resulted in the discovery of thousands of islands spread across an enormous area of the Pacific Ocean. Beginning as early as approximately 3500 cal. B.P. in Western Micronesia, populations began an expansion westward eventually settling East Polynesia over two millennia later. Although this general pattern is well-established, the reliability of colonization chronologies for particular islands and island groups varies significantly. This chapter synthesizes and critiques current interpretations of radiocarbon and other dating estimates for colonization of the major islands across the region and provides recommendations for future research and chronology building, highlighting the potential for Bayesian analyses. Estimates for the colonization of Hawai'i are presented as a case study.

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