Gotowe bibliografie tematyczne / Bayes's theorem

Gotowa bibliografia na temat „Bayes's theorem”

Autor: Grafiati
Data publikacji: 25 lipca 2024

Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych

Wybierz rodzaj źródła:

Spis treści

Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Bayes's theorem”.

Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.

Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.

Artykuły w czasopismach na temat "Bayes's theorem"

1

Utyuganova, V. V., V. S. Serdyuk i A. I. Fomin. "Prediction and Assessment of the Occupational Risks in the Mining Industry Using the Bayess Theorem". Occupational Safety in Industry, nr 1 (styczeń 2021): 79–87. http://dx.doi.org/10.24000/0409-2961-2021-1-79-87.

Pełny tekst źródła
Streszczenie:
The analysis of existing methods for assessing occupational risks is carried out, and the need for searchinga fundamentally new approach to the assessment and prediction of risks in the mining industry is substantiated. Based on the results of the analysis of modern methods and technologies, it is established that the development of the methodology for assessment and prediction of the occupational risks using Bayes's theorem has significant advantages: simplicity and accessibility for the occupational safety specialists, reproducibility considering many factors of working conditions, as well as the possibility of preventive measures prediction and development. The application of Bayes's theorem is promising in determining cause-and-effect relationships and predicting the occupational morbidity of the employees, which is also an advantage of this methodology for managing occupational risks in the mining industry. Bayes's approaches to modeling are characterized by high performance, intuitively clear in the form of a graph. The example is given concerning the application of Bayes's theorem to assess the risk of a fatal incident taking into account the statistics on the mining industry. Also, the simplest types of Bayes’s trust networks were developed reflecting the possibility of establishing cause-and-effect relationships (both for assessment and prediction), and are the basis for further modeling.
Style APA, Harvard, Vancouver, ISO itp.
2

Eells, E. "Review: Bayes's Theorem". Mind 113, nr 451 (1.07.2004): 591–96. http://dx.doi.org/10.1093/mind/113.451.591.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
3

McGrew, T. "Two cheers for Bayes's theorem". Analysis 55, nr 2 (1.04.1995): 123–25. http://dx.doi.org/10.1093/analys/55.2.123.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

CadwalladerOlsker, Todd D. "When 95% Accurate Isn't: Exploring Bayes's Theorem". Mathematics Teacher 104, nr 6 (luty 2011): 426–31. http://dx.doi.org/10.5951/mt.104.6.0426.

Pełny tekst źródła
Streszczenie:
Bayes's theorem is notorious for being a difficult topic to learn and to teach. Problems involving Bayes's theorem (either implicitly or explicitly) generally involve calculations based on two or more given probabilities and their complements. Further, a correct solution depends on students' ability to interpret the problem correctly. Shaughnessy (1992) has commented, “There is a good deal of cognitive strain involved in reading the problem and keeping everything straight; it is difficult for students to interpret exactly what they are being asked to do” (p. 471).
Style APA, Harvard, Vancouver, ISO itp.
5

CadwalladerOlsker, Todd D. "When 95% Accurate Isn't: Exploring Bayes's Theorem". Mathematics Teacher 104, nr 6 (luty 2011): 426–31. http://dx.doi.org/10.5951/mt.104.6.0426.

Pełny tekst źródła
Streszczenie:
Bayes's theorem is notorious for being a difficult topic to learn and to teach. Problems involving Bayes's theorem (either implicitly or explicitly) generally involve calculations based on two or more given probabilities and their complements. Further, a correct solution depends on students' ability to interpret the problem correctly. Shaughnessy (1992) has commented, “There is a good deal of cognitive strain involved in reading the problem and keeping everything straight; it is difficult for students to interpret exactly what they are being asked to do” (p. 471).
Style APA, Harvard, Vancouver, ISO itp.
6

Zellner, Arnold. "Optimal Information Processing and Bayes's Theorem". American Statistician 42, nr 4 (listopad 1988): 278. http://dx.doi.org/10.2307/2685143.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
7

Zellner, Arnold. "Optimal Information Processing and Bayes's Theorem". American Statistician 42, nr 4 (listopad 1988): 278–80. http://dx.doi.org/10.1080/00031305.1988.10475585.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
8

Jaynes, E. T. "[Optimal Information Processing and Bayes's Theorem]: Comment". American Statistician 42, nr 4 (listopad 1988): 280. http://dx.doi.org/10.2307/2685144.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

Hill, Bruce M. "[Optimal Information Processing and Bayes's Theorem]: Comment". American Statistician 42, nr 4 (listopad 1988): 281. http://dx.doi.org/10.2307/2685145.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Zellner, Arnold. "[Optimal Information Processing and Bayes's Theorem]: Reply". American Statistician 42, nr 4 (listopad 1988): 283. http://dx.doi.org/10.2307/2685148.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
Więcej źródeł

Rozprawy doktorskie na temat "Bayes's theorem"

1

Portugal, Agnaldo Cuoco. "Theism, Bayes's theorem and religious experience : an examination of Richard Swinburnes's religious epistemology". Thesis, King's College London (University of London), 2003. https://kclpure.kcl.ac.uk/portal/en/theses/theism-bayess-theorem-and-religious-experience--an-examination-of-richard-swinburness-religious-epistemology(f6ab0fd9-9277-41d7-9997-ecad803c54ae).html.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

Rogers, David M. "Using Bayes' theorem for free energy calculations". Cincinnati, Ohio : University of Cincinnati, 2009. http://rave.ohiolink.edu/etdc/view.cgi?acc_num=ucin1251832030.

Pełny tekst źródła
Streszczenie:
Thesis (Ph. D.)--University of Cincinnati, 2009.
Advisor: Thomas L. Beck. Title from electronic thesis title page (viewed Jan. 21, 2010). Keywords: Bayes; probability; statistical mechanics; free energy. Includes abstract. Includes bibliographical references.
Style APA, Harvard, Vancouver, ISO itp.
3

Jones, Martin K. "Bayes' Theorem and positive confirmation : an experimental economic analysis". Thesis, University of East Anglia, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300072.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

Fletcher, Douglas. "Generalized Empirical Bayes: Theory, Methodology, and Applications". Diss., Temple University Libraries, 2019. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/546485.

Pełny tekst źródła
Streszczenie:
Statistics
Ph.D.
The two key issues of modern Bayesian statistics are: (i) establishing a principled approach for \textit{distilling} a statistical prior distribution that is \textit{consistent} with the given data from an initial believable scientific prior; and (ii) development of a \textit{consolidated} Bayes-frequentist data analysis workflow that is more effective than either of the two separately. In this thesis, we propose generalized empirical Bayes as a new framework for exploring these fundamental questions along with a wide range of applications spanning fields as diverse as clinical trials, metrology, insurance, medicine, and ecology. Our research marks a significant step towards bridging the ``gap'' between Bayesian and frequentist schools of thought that has plagued statisticians for over 250 years. Chapters 1 and 2---based on \cite{mukhopadhyay2018generalized}---introduces the core theory and methods of our proposed generalized empirical Bayes (gEB) framework that solves a long-standing puzzle of modern Bayes, originally posed by Herbert Robbins (1980). One of the main contributions of this research is to introduce and study a new class of nonparametric priors ${\rm DS}(G, m)$ that allows exploratory Bayesian modeling. However, at a practical level, major practical advantages of our proposal are: (i) computational ease (it does not require Markov chain Monte Carlo (MCMC), variational methods, or any other sophisticated computational techniques); (ii) simplicity and interpretability of the underlying theoretical framework which is general enough to include almost all commonly encountered models; and (iii) easy integration with mainframe Bayesian analysis that makes it readily applicable to a wide range of problems. Connections with other Bayesian cultures are also presented in the chapter. Chapter 3 deals with the topic of measurement uncertainty from a new angle by introducing the foundation of nonparametric meta-analysis. We have applied the proposed methodology to real data examples from astronomy, physics, and medical disciplines. Chapter 4 discusses some further extensions and application of our theory to distributed big data modeling and the missing species problem. The dissertation concludes by highlighting two important areas of future work: a full Bayesian implementation workflow and potential applications in cybersecurity.
Temple University--Theses
Style APA, Harvard, Vancouver, ISO itp.
5

Conlon, Erin Marie. "Estimation and flexible correlation structures in spatial hierarchical models of disease mapping /". Diss., ON-CAMPUS Access For University of Minnesota, Twin Cities Click on "Connect to Digital Dissertations", 1999. http://www.lib.umn.edu/articles/proquest.phtml.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
6

Chadwick, Thomas Jonathan. "A general Bayes theory of nested model comparisons". Thesis, University of Newcastle Upon Tyne, 2002. http://hdl.handle.net/10443/641.

Pełny tekst źródła
Streszczenie:
We propose a general Bayes analysis for nested model comparisons which does not suffer from Lindley's paradox. It does not use Bayes factors, but uses the posterior distribution of the likelihood ratio between the models evaluated at the true values of the nuisance parameters. This is obtained directly from the posterior distribution of the full model parameters. The analysis requires only conventional uninformative or flat priors, and prior odds on the models. The conclusions from the posterior distribution of the likelihood ratio are in general in conflict with Bayes factor conclusions, but are in agreement with frequentist likelihood ratio test conclusions. Bayes factor conclusions and those from the BIC are, even in simple cases, in conflict with conclusions from HPD intervals for the same parameters, and appear untenable in general. Examples of the new analysis are given, with comparisons to classical P-values and Bayes factors.
Style APA, Harvard, Vancouver, ISO itp.
7

Zhang, Shunpu. "Some contributions to empirical Bayes theory and functional estimation". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23100.pdf.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
8

Yang, Ying. "Discretization for Naive-Bayes learning". Monash University, School of Computer Science and Software Engineering, 2003. http://arrow.monash.edu.au/hdl/1959.1/9393.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

Liu, Ka-yee. "Bayes and empirical Bayes estimation for the panel threshold autoregressive model and non-Gaussian time series". Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B30706166.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Liu, Ka-yee, i 廖家怡. "Bayes and empirical Bayes estimation for the panel threshold autoregressive model and non-Gaussian time series". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B30706166.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
Więcej źródeł

Książki na temat "Bayes's theorem"

1

Richard, Swinburne, i British Academy, red. Bayes's theorem. Oxford: Published for The British Academy by Oxford University Press, 2002.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

Proving history: Bayes's theorem and the quest for the historical Jesus. Amherst, N.Y: Prometheus Books, 2012.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
3

Kuo, Lynn. Bayesian computations in survival models via the Gibbs sampler. Monterey, Calif: Naval Postgraduate School, 1991.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

Kucsma, András I. Bidding for contract games: Applying game theory to analyze first price sealed bid auctions. Monterey, Calif: Naval Postgraduate School, 1997.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
5

Gaver, Donald Paul. Regression analysis of hierarchical Poisson-like event rate data: Superpopulation model effect on predictions. Monterey, Calif: Naval Postgraduate School, 1990.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
6

ERIC Clearinghouse on Assessment and Evaluation., red. Bayes' theorem: An old tool applicable to today's classroom measurement needs. [College Park, MD: ERIC Clearinghouse on Assessment and Evaluation, University of Maryland, 2000.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
7

Carlin, Bradley P. Bayes and empirical Bayes methods for data analysis. Boca Raton: Chapman & Hall/CRC, 1998.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
8

Carlin, Bradley P. Bayes and Empirical Bayes methods for data analysis. Wyd. 2. Boca Raton: Chapman & Hall/CRC, 2000.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

1944-, Louis Thomas A., red. Bayes and empirical Bayes methods for data analysis. London: Chapman & Hall, 1996.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Large-scale inference: Empirical Bayes methods for estimation, testing, and prediction. Cambridge: Cambridge University Press, 2010.

Znajdź pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
Więcej źródeł

Części książek na temat "Bayes's theorem"

1

Modis, Konstantinos. "Bayes’s Theorem". W Encyclopedia of Mathematical Geosciences, 1–4. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_440-1.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

Modis, Konstantinos. "Bayes’s Theorem". W Encyclopedia of Mathematical Geosciences, 61–65. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_440.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
3

O’Hagan, Anthony. "Bayes’ theorem". W Probability, 45–61. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1211-3_3.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

Harney, Hanns Ludwig. "Bayes’ Theorem". W Bayesian Inference, 11–25. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41644-1_2.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
5

Petroianu, Georg, i Peter Michael Osswald. "Bayes-Theorem". W Anästhesie in Frage und Antwort, 31–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-05715-5_11.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
6

Harney, Hanns L. "Bayes’ Theorem". W Bayesian Inference, 8–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-06006-3_2.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
7

Hoang, Lê Nguyên. "Bayes’ Theorem". W The Equation of Knowledge, 17–32. Boca Raton : C&H/CRC Press, 2020. | Translation of: La formule du savoir : une philosophie unifiée du savoir fondée sur le théorème de Bayes: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9780367855307-2.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
8

Koch, Karl-Rudolf. "Bayes’ Theorem". W Bayesian Inference with Geodetic Applications, 4–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/bfb0048702.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

Kadane, Joseph B. "Bayes’ Theorem". W International Encyclopedia of Statistical Science, 89–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_141.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Gooch, Jan W. "Bayes’ Theorem". W Encyclopedic Dictionary of Polymers, 970. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15157.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.

Streszczenia konferencji na temat "Bayes's theorem"

1

Dezert, Jean, Albena Tchamova i Deqiang Han. "Total Belief Theorem and Generalized Bayes' Theorem". W 2018 International Conference on Information Fusion (FUSION). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455351.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

Price, Harold J. "Uninformative priors for Bayes’ theorem". W BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING. AIP, 2002. http://dx.doi.org/10.1063/1.1477060.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
3

Ballesteros-Pérez, Pablo, Mª Carmen González-Cruz i Daniel Mora-Melià. "EXPLAINING THE BAYES’ THEOREM GRAPHICALLY". W 12th International Technology, Education and Development Conference. IATED, 2018. http://dx.doi.org/10.21125/inted.2018.0028.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

Josang, Audun. "Generalising Bayes' theorem in subjective logic". W 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI). IEEE, 2016. http://dx.doi.org/10.1109/mfi.2016.7849531.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
5

Kosko, Bart. "Bayes Theorem Extends to Overlapping Hypotheses". W 2019 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2019. http://dx.doi.org/10.1109/csci49370.2019.00106.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
6

Qu, Guangzhi, Hui Zhang i Craig T. Hartrick. "Multi-label classification with Bayes' theorem". W 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2011. http://dx.doi.org/10.1109/bmei.2011.6098780.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
7

Xiao, Mi, Qiangzhuang Yao, Liang Gao, Haihong Xiong i Fengxiang Wang. "Metamodel Uncertainty Quantification by Using Bayes’ Theorem". W ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46746.

Pełny tekst źródła
Streszczenie:
In complex engineering systems, approximation models, also called metamodels, are extensively constructed to replace the computationally expensive simulation and analysis codes. With different sample data and metamodeling methods, different metamodels can be constructed to describe the behavior of an engineering system. Then, metamodel uncertainty will arise from selecting the best metamodel from a set of alternative ones. In this study, a method based on Bayes’ theorem is used to quantify this metamodel uncertainty. With some mathematical examples, metamodels are built by six metamodeling methods, i.e., polynomial response surface, locally weighted polynomials (LWP), k-nearest neighbors (KNN), radial basis functions (RBF), multivariate adaptive regression splines (MARS), and kriging methods, and under four sampling methods, i.e., parameter study (PS), Latin hypercube sampling (LHS), optimal LHS and full factorial design (FFD) methods. The uncertainty of metamodels created by different metamodeling methods and under different sampling methods is quantified to demonstrate the process of implementing the method.
Style APA, Harvard, Vancouver, ISO itp.
8

Liu, Hongze, Zhengjiang Liu, Xin Wang i Yao Cai. "Bayes' Theorem based maritime safety information classifier". W 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407588.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

Li, Jiandun, Dingyu Yang i Chunlei Ji. "Mine weighted network motifs via Bayes' theorem". W 2017 4th International Conference on Systems and Informatics (ICSAI). IEEE, 2017. http://dx.doi.org/10.1109/icsai.2017.8248334.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Dezert, Jean, Albena Tchamova, Deqiang Han i Thanuka Wickramarathne. "A Simplified Formulation of Generalized Bayes' Theorem". W 2019 22th International Conference on Information Fusion (FUSION). IEEE, 2019. http://dx.doi.org/10.23919/fusion43075.2019.9011357.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.

Raporty organizacyjne na temat "Bayes's theorem"

1

Smith, A. F., i A. E. Gelfand. Bayes Theorem from a Sampling-Resampling Perspective. Fort Belvoir, VA: Defense Technical Information Center, lipiec 1991. http://dx.doi.org/10.21236/ada239515.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

Smith, Donald L., Denise Neudecker i Roberto Capote Noy. Investigation of the Effects of Probability Density Function Kurtosis on Evaluated Data Results. IAEA Nuclear Data Section, maj 2018. http://dx.doi.org/10.61092/iaea.yxma-3y50.

Pełny tekst źródła
Streszczenie:
In two previous investigations that are documented in this IAEA report series, we examined the effects of non-Gaussian, non-symmetric probability density functions (PDFs) on the outcomes of data evaluations. Most of this earlier work involved considering just two independent input data values and their respective uncertainties. They were used to generate one evaluated data point. The input data are referred to, respectively, as the mean value and standard deviation pair (y0,s0) for a prior PDF p0(y) and a second mean value and standard deviation pair (ye,se) for a likelihood PDF pe(y). Conceptually, these input data could be viewed as resulting from theory (subscript “0”) and experiment (subscript “e”). In accordance with Bayes Theorem, the evaluated mean value and standard deviation pair (ysol,ssol) corresponds to the posterior PDF p(y) which is related to p0(y) and pe(y) by p(y) = Cp0(y)pe(y). The prior and likelihood PDFs are both assumed to be normalized so that they integrate to unity for all y ≥ 0. Negative values of y are viewed as non-physical so they are not permitted. The product function p0(y)pe(y) is not normalized, so a positive multiplicative constant C is required to normalize p(y). In the earlier work, both normal (Gaussian) and lognormal functions were considered for the prior PDF. The likelihood functions were all taken to be Gaussians. Gaussians are symmetric, with zero skewness, and they always possess a fixed kurtosis of 3. Lognormal functions are inherently skewed, with widely varying values of skewness and kurtosis that depend on the function parameters. In order to explore the effects of kurtosis, distinct from skewness, the present work constrains the likelihood function to be Gaussian, and it considers three distinct, inherently symmetric prior PDF types: Gaussian (kurtosis = 3), Continuous Uniform (kurtosis = 1.8), and Laplace (kurtosis = 6). A product of two Gaussians produces a Gaussian even if ye ≠ y0. The product of a Gaussian PDF and a Uniform PDF, or a Laplace PDF, yields a symmetric PDF with zero skewness only when ye = y0. A pure test of the effect of kurtosis on an evaluation is provided by considering combinations of s0 and se with ye = y0. The present work also investigates the extent to which p(y) exhibits skewness when ye ≠ y0, again by considering various values for s0 and se. The Bayesian results from numerous numerical examples have been compared with corresponding least-squares solutions in order to arrive at some general conclusions regarding how the evaluated result (ysol,ssol) depends on various combinations of the input data y0, s0, ye, and se as well as on prior-likelihood PDF combinations: Gaussian-Gaussian, Uniform-Gaussian, and Laplace-Gaussian.
Style APA, Harvard, Vancouver, ISO itp.
3

Smith, Donald L., Denise Neudecker i Roberto Capote Noy. Investigation of the Effects of Probability Density Function Kurtosis on Evaluated Data Results. IAEA Nuclear Data Section, maj 2020. http://dx.doi.org/10.61092/iaea.nqsh-f02d.

Pełny tekst źródła
Streszczenie:
In two previous investigations that are documented in this IAEA report series, we examined the effects of non-Gaussian, non-symmetric probability density functions (PDFs) on the outcomes of data evaluations. Most of this earlier work involved considering just two independent input data values and their respective uncertainties. They were used to generate one evaluated data point. The input data are referred to, respectively, as the mean value and standard deviation pair (y0,s0) for a prior PDF p0(y) and a second mean value and standard deviation pair (ye,se) for a likelihood PDF pe(y). Conceptually, these input data could be viewed as resulting from theory (subscript “0”) and experiment (subscript “e”). In accordance with Bayes Theorem, the evaluated mean value and standard deviation pair (ysol,ssol) corresponds to the posterior PDF p(y) which is related to p0(y) and pe(y) by p(y) = Cp0(y)pe(y). The prior and likelihood PDFs are both assumed to be normalized so that they integrate to unity for all y ≥ 0. Negative values of y are viewed as non-physical so they are not permitted. The product function p0(y)pe(y) is not normalized, so a positive multiplicative constant C is required to normalize p(y). In the earlier work, both normal (Gaussian) and lognormal functions were considered for the prior PDF. The likelihood functions were all taken to be Gaussians. Gaussians are symmetric, with zero skewness, and they always possess a fixed kurtosis of 3. Lognormal functions are inherently skewed, with widely varying values of skewness and kurtosis that depend on the function parameters. In order to explore the effects of kurtosis, distinct from skewness, the present work constrains the likelihood function to be Gaussian, and it considers three distinct, inherently symmetric prior PDF types: Gaussian (kurtosis = 3), Continuous Uniform (kurtosis = 1.8), and Laplace (kurtosis = 6). A product of two Gaussians produces a Gaussian even if ye ≠ y0. The product of a Gaussian PDF and a Uniform PDF, or a Laplace PDF, yields a symmetric PDF with zero skewness only when ye = y0. A pure test of the effect of kurtosis on an evaluation is provided by considering combinations of s0 and se with ye = y0. The present work also investigates the extent to which p(y) exhibits skewness when ye ≠ y0, again by considering various values for s0 and se. The Bayesian results from numerous numerical examples have been compared with corresponding least-squares solutions in order to arrive at some general conclusions regarding how the evaluated result (ysol,ssol) depends on various combinations of the input data y0, s0, ye, and se as well as on prior-likelihood PDF combinations: Gaussian-Gaussian, Uniform-Gaussian, and Laplace-Gaussian.
Style APA, Harvard, Vancouver, ISO itp.
4

Smith, D. L., D. Neudecker i R. Capote Noy. Investigation of the Effects of Probability Density Function Kurtosis on Evaluated Data Results. IAEA Nuclear Data Section, maj 2020. http://dx.doi.org/10.61092/iaea.3ar5-xmp8.

Pełny tekst źródła
Streszczenie:
In two previous investigations that are documented in this IAEA report series, we examined the effects of non-Gaussian, non-symmetric probability density functions (PDFs) on the outcomes of data evaluations. Most of this earlier work involved considering just two independent input data values and their respective uncertainties. They were used to generate one evaluated data point. The input data are referred to, respectively, as the mean value and standard deviation pair (y0,s0) for a prior PDF p0(y) and a second mean value and standard deviation pair (ye,se) for a likelihood PDF pe(y). Conceptually, these input data could be viewed as resulting from theory (subscript “0”) and experiment (subscript “e”). In accordance with Bayes Theorem, the evaluated mean value and standard deviation pair (ysol,ssol) corresponds to the posterior PDF p(y) which is related to p0(y) and pe(y) by p(y) = Cp0(y)pe(y). The prior and likelihood PDFs are both assumed to be normalized so that they integrate to unity for all y ≥ 0. Negative values of y are viewed as non-physical so they are not permitted. The product function p0(y)pe(y) is not normalized, so a positive multiplicative constant C is required to normalize p(y). In the earlier work, both normal (Gaussian) and lognormal functions were considered for the prior PDF. The likelihood functions were all taken to be Gaussians. Gaussians are symmetric, with zero skewness, and they always possess a fixed kurtosis of 3. Lognormal functions are inherently skewed, with widely varying values of skewness and kurtosis that depend on the function parameters. In order to explore the effects of kurtosis, distinct from skewness, the present work constrains the likelihood function to be Gaussian, and it considers three distinct, inherently symmetric prior PDF types: Gaussian (kurtosis = 3), Continuous Uniform (kurtosis = 1.8), and Laplace (kurtosis = 6). A product of two Gaussians produces a Gaussian even if ye ≠ y0. The product of a Gaussian PDF and a Uniform PDF, or a Laplace PDF, yields a symmetric PDF with zero skewness only when ye = y0. A pure test of the effect of kurtosis on an evaluation is provided by considering combinations of s0 and se with ye = y0. The present work also investigates the extent to which p(y) exhibits skewness when ye ≠ y0, again by considering various values for s0 and se. The Bayesian results from numerous numerical examples have been compared with corresponding least-squares solutions in order to arrive at some general conclusions regarding how the evaluated result (ysol,ssol) depends on various combinations of the input data y0, s0, ye, and se as well as on prior-likelihood PDF combinations: Gaussian-Gaussian, Uniform-Gaussian, and Laplace-Gaussian.
Style APA, Harvard, Vancouver, ISO itp.
Możesz być także zainteresowany rozszerzonymi bibliografiami na temat „Bayes's theorem” dla poszczególnych typów źródeł:
Artykuły w czasopismach Rozprawy doktorskie Książki
Oferujemy zniżki na wszystkie plany premium dla autorów, których prace zostały uwzględnione w tematycznych zestawieniach literatury. Skontaktuj się z nami, aby uzyskać unikalny kod promocyjny!

Do bibliografii