Academic literature on the topic 'Uniform prior'
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Journal articles on the topic "Uniform prior"
Hartigan, J. A. "Locally uniform prior distributions." Annals of Statistics 24, no. 1 (February 1996): 160–73. http://dx.doi.org/10.1214/aos/1033066204.
Full textShulman, N., and M. Feder. "The Uniform Distribution as a Universal Prior." IEEE Transactions on Information Theory 50, no. 6 (June 2004): 1356–62. http://dx.doi.org/10.1109/tit.2004.828152.
Full textvan Zwet, Erik. "A default prior for regression coefficients." Statistical Methods in Medical Research 28, no. 12 (December 13, 2018): 3799–807. http://dx.doi.org/10.1177/0962280218817792.
Full textKulawik, S. S., K. W. Bowman, M. Luo, C. D. Rodgers, and L. Jourdain. "Impact of nonlinearity on changing the a priori of trace gas profile estimates from the Tropospheric Emission Spectrometer (TES)." Atmospheric Chemistry and Physics 8, no. 12 (June 20, 2008): 3081–92. http://dx.doi.org/10.5194/acp-8-3081-2008.
Full textMukhopadhyay, S., and M. Ghosh. "On the Uniform Approximation of Laplace′s Prior by t-Priors in Location Problems." Journal of Multivariate Analysis 54, no. 2 (August 1995): 284–94. http://dx.doi.org/10.1006/jmva.1995.1057.
Full textKulawik, S. S., K. W. Bowman, M. Luo, C. D. Rodgers, and L. Jourdain. "Technical Note: Impact of nonlinearity on changing the a priori of trace gas profiles estimates from the Tropospheric Emission Spectrometer (TES)." Atmospheric Chemistry and Physics Discussions 8, no. 1 (January 25, 2008): 1261–89. http://dx.doi.org/10.5194/acpd-8-1261-2008.
Full textTak, H. "Frequency coverage properties of a uniform shrinkage prior distribution." Journal of Statistical Computation and Simulation 87, no. 15 (July 8, 2017): 2929–39. http://dx.doi.org/10.1080/00949655.2017.1349769.
Full textDi, Ruohai, Peng Wang, Chuchao He, and Zhigao Guo. "Constrained Adjusted Maximum a Posteriori Estimation of Bayesian Network Parameters." Entropy 23, no. 10 (September 30, 2021): 1283. http://dx.doi.org/10.3390/e23101283.
Full textCunanan, Kristen M., Alexia Iasonos, Ronglai Shen, and Mithat Gönen. "Variance prior specification for a basket trial design using Bayesian hierarchical modeling." Clinical Trials 16, no. 2 (December 7, 2018): 142–53. http://dx.doi.org/10.1177/1740774518812779.
Full textZhu, Hai, Xia Luo, Yanjin Li, Ying Zhu, and Qian Huang. "Comparing the efficiency and robustness of state-of-the-art experimental designs for stated choice modeling: A simulation analysis." Advances in Mechanical Engineering 9, no. 2 (February 2017): 168781401769189. http://dx.doi.org/10.1177/1687814017691894.
Full textDissertations / Theses on the topic "Uniform prior"
Righi, Ali. "Sur l'estimation de densités prédictives et l'estimation d'un coût." Rouen, 2011. http://www.theses.fr/2011ROUES002.
Full textThis thesis is divided in two parts. In the first part, we investigate predictive density estimation for a multivariate Gaussian model under the Kullback-Leibler loss. We focus on the link with the problem of estimation of the mean under quadratic loss. We obtain several parallel results. We prove minimaxity and improved estimation results under restriction for the unknown mean. In particular, we show, via two different paths, that the Bayesian predictive density associated to the uniform prior on a convex C dominates the best invariant predictive density when μ 2 C. This is a parallel result to Hartigan’s result in 2004, for the estimation of the mean under quadratic loss. At the end of this part, we give numerical simulations to visualize the gain obtained by some of our new proposed estimators. In the second part, for the Gaussian model of dimension p, we treat the problem of estimating the loss of the standard estimator of the mean (that is, #0(X) = X). We give generalized Bayes estimators which dominate the unbiased estimator of loss (that is, #0(X) = p), through sufficient conditions for p # 5. Examples illustrate the theory. Then we carry on a technical study and numerical simulations on the gain reached by one of our proposed minimax generalized Bayes estimators of loss
Floropoulos, Theodore C. "A Bayesian method to improve sampling in weapons testing." Thesis, 1988. http://hdl.handle.net/10945/22930.
Full textThis thesis describes a Bayesian method to determine the number of samples needed to estimate a proportion or probability with 95% confidence when prior bounds are placed on that proportion. It uses the Uniform [a,b] distribution as the prior, and develops a computer program and tables to find the sample size. Tables and examples are also given to compare these results with other approaches for finding sample size. The improvement that can be obtained with this method is fewer samples, and consequently less cost in Weapons Testing is required to meet a desired confidence size for a proportion or probability.
http://archive.org/details/bayesianmethodto00flor
Lieutenant Commander, Hellenic Navy
Yu, Ting-Ta, and 余庭達. "On the Optimum Quantum Detection for the Ternary Geometrically Uniform Pure State Signal with Unequal Prior Probability." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/85178959322928165739.
Full text國立清華大學
電機工程學系
96
This thesis concerns the quantum detection problem for ternary pure state signals. We first review the relevant study on the quantum signal detection problem in the manner determined in Eldar's paper. We verify her result with the ternary geometrically uniform (GU) pure state signal having the uniform prior probability distribution, in which we have used the matrix-form expression of the optimum detection operators. Next, we consider the optimum detection problem for the ternary GU pure state signal under the condition that one prior probability is given and the others are unknown. In this situation, we formulate our optimization problem and derive the necessary and sufficient conditions for the solution of the problem. To seek the closed-form expression for the optimum detection operators, we perform the numerical simulation. As a result, we make a conjecture on the closed-form expression of the optimum measurement operators and on the optimum prior distribution for our problem.
Tuyl, Frank Adrianus Wilhelmus Maria. "Estimation of the Binomial parameter: in defence of Bayes (1763)." Thesis, 2007. http://hdl.handle.net/1959.13/25730.
Full textInterval estimation of the Binomial parameter è, representing the true probability of a success, is a problem of long standing in statistical inference. The landmark work is by Bayes (1763) who applied the uniform prior to derive the Beta posterior that is the normalised Binomial likelihood function. It is not well known that Bayes favoured this ‘noninformative’ prior as a result of considering the observable random variable x as opposed to the unknown parameter è, which is an important difference. In this thesis we develop additional arguments in favour of the uniform prior for estimation of è. We start by describing the frequentist and Bayesian approaches to interval estimation. It is well known that for common continuous models, while different in interpretation, frequentist and Bayesian intervals are often identical, which is directly related to the existence of a pivotal quantity. The Binomial model, and its Poisson sister also, lack a pivotal quantity, despite having sufficient statistics. Lack of a pivotal quantity is the reason why there is no consensus on one particular estimation method, more so than its discreteness: frequentist (unconditional) coverage depends on è. Exact methods guarantee minimum coverage to be at least equal to nominal and approximate methods aim for mean coverage to be close to nominal. We agree with what seems like the majority of frequentists, that exact methods are too conservative in practice, and show additional undesirable properties. This includes more recent ‘short’ exact intervals. We argue that Bayesian intervals based on noninformative priors are preferable to the family of frequentist approximate intervals, some of which are wider than exact intervals for particular data values. A particular property of the interval based on the uniform prior is that its mean coverage is exactly equal to nominal. However, once committed to the Bayesian approach there is no denying that the current preferred choice, by ‘objective’ Bayesians, is the U-shaped Jeffreys prior which results from various methods aimed at finding noninformative priors. The most successful such method seems to be reference analysis which has led to sensible priors in previously unsolved problems, concerning multiparameter models that include ‘nuisance’ parameters. However, we argue that there is a class of models for which the Jeffreys/reference prior may be suboptimal and that in the case of the Binomial distribution the requirement of a uniform prior predictive distribution leads to a more reasonable ‘consensus’ prior.
Tuyl, Frank Adrianus Wilhelmus Maria. "Estimation of the Binomial parameter: in defence of Bayes (1763)." 2007. http://hdl.handle.net/1959.13/25730.
Full textInterval estimation of the Binomial parameter è, representing the true probability of a success, is a problem of long standing in statistical inference. The landmark work is by Bayes (1763) who applied the uniform prior to derive the Beta posterior that is the normalised Binomial likelihood function. It is not well known that Bayes favoured this ‘noninformative’ prior as a result of considering the observable random variable x as opposed to the unknown parameter è, which is an important difference. In this thesis we develop additional arguments in favour of the uniform prior for estimation of è. We start by describing the frequentist and Bayesian approaches to interval estimation. It is well known that for common continuous models, while different in interpretation, frequentist and Bayesian intervals are often identical, which is directly related to the existence of a pivotal quantity. The Binomial model, and its Poisson sister also, lack a pivotal quantity, despite having sufficient statistics. Lack of a pivotal quantity is the reason why there is no consensus on one particular estimation method, more so than its discreteness: frequentist (unconditional) coverage depends on è. Exact methods guarantee minimum coverage to be at least equal to nominal and approximate methods aim for mean coverage to be close to nominal. We agree with what seems like the majority of frequentists, that exact methods are too conservative in practice, and show additional undesirable properties. This includes more recent ‘short’ exact intervals. We argue that Bayesian intervals based on noninformative priors are preferable to the family of frequentist approximate intervals, some of which are wider than exact intervals for particular data values. A particular property of the interval based on the uniform prior is that its mean coverage is exactly equal to nominal. However, once committed to the Bayesian approach there is no denying that the current preferred choice, by ‘objective’ Bayesians, is the U-shaped Jeffreys prior which results from various methods aimed at finding noninformative priors. The most successful such method seems to be reference analysis which has led to sensible priors in previously unsolved problems, concerning multiparameter models that include ‘nuisance’ parameters. However, we argue that there is a class of models for which the Jeffreys/reference prior may be suboptimal and that in the case of the Binomial distribution the requirement of a uniform prior predictive distribution leads to a more reasonable ‘consensus’ prior.
Chen, Hsiang-Chun. "Inference for Clustered Mixed Outcomes from a Multivariate Generalized Linear Mixed Model." Thesis, 2013. http://hdl.handle.net/1969.1/151145.
Full textHuang, Cheng-Jyun, and 黃程鈞. "A priori uniform estimates for an interface problem from composite media with anisotropic periodic fibres." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/06585777399663562634.
Full text國立交通大學
應用數學系所
104
我們關心非均勻橢圓方程在介面附近的解的均勻估計。這個方程式描述了 在異質媒介中電流 (熱、速度等) 的行為。其中,異質媒介是具各向異性的傳導 纖維嵌入的各向同性的方陣。詳細的說,我們考慮的是嵌入了具我們所關心的 各向異性傳導纖維 (通過介面方向的傳導系數與在沿纖維方向的傳導系數的比值 小於 1) 的雙面多孔類型區域 (見 Figure 3)。在通過介面的方向上,纖維對於方 陣的傳導系數比值記作 ϵ ∈ (0,1)。我們得到在介面附近的解的先驗均勻 Hölder 估計,還有在介面附近的梯度 Hölder 估計。但是在估計中的係數與 ε^(-1) 有關。 為了凸顯出 ϵ −1 的作用,我們精確的寫出在 Hölder 估計中 ε^(-1) 的次方數。
Gueye, N'deye Rokhaya. "Problèmes d'estimation de paramètres avec restriction sur l'espace des paramètres." Thèse, 2003. http://hdl.handle.net/1866/14587.
Full textPerret, Stéphane. "Localisation, reconstruction et mosaïque appliquées aux peintures sur cylindres généralisés à axe droit en vision monoculaire." Phd thesis, 1997. http://tel.archives-ouvertes.fr/tel-00004961.
Full textBook chapters on the topic "Uniform prior"
Wang, Guodong, Bin Wei, Zhenkuan Pan, Jingge Lu, and Zhaojing Diao. "Non-uniform Motion Deblurring Using Normalized Hyper Laplacian Prior." In Communications in Computer and Information Science, 103–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48558-3_11.
Full textLekdee, Krisada, Chao Yang, Lily Ingsrisawang, and Yisheng Li. "A Uniform Shrinkage Prior in Spatiotemporal Poisson Models for Count Data." In Emerging Topics in Statistics and Biostatistics, 83–102. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72437-5_4.
Full textTamaki, Mitsushi, and Qi Wang. "A Random Arrival Time Best-Choice Problem with Uniform Prior on the Number of Arrivals." In Springer Optimization and Its Applications, 499–510. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-89496-6_24.
Full textCheng, Yougan, Ronny Straube, Abed E. Alnaif, Lu Huang, Tarek A. Leil, and Brian J. Schmidt. "Virtual Populations for Quantitative Systems Pharmacology Models." In Methods in Molecular Biology, 129–79. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2265-0_8.
Full textPettigrew, Richard. "Priors that Allow You to Learn Inductively." In Epistemic Risk and the Demands of Rationality, 175–82. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192864352.003.0011.
Full textDonovan, Therese M., and Ruth M. Mickey. "Probability Density Functions." In Bayesian Statistics for Beginners, 108–30. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198841296.003.0009.
Full textAhranjani, Maryam. "Erecting a Virtual Schoolhouse Gate." In Advances in Electronic Government, Digital Divide, and Regional Development, 73–89. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8350-9.ch004.
Full textRicketson, Sam, and Jane C. Ginsburg. "Origins of the Berne Convention." In International Copyright and Neighbouring Rights, 38–76. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198801986.003.0002.
Full textOstwald, Kai, and Tun Myint. "Myanmar: Pandemic in a Time of Transition." In Covid-19 in Asia, 335–48. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197553831.003.0023.
Full textLenka, Rasmita, Asimananda Khandual, Koustav Dutta, and Soumya Ranjan Nayak. "Image Enhancement." In Examining Fractal Image Processing and Analysis, 211–23. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0066-8.ch011.
Full textConference papers on the topic "Uniform prior"
Rademacher, Paul, and Milos Doroslovacki. "Bayesian Learning for Classification using a Uniform Dirichlet Prior." In 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2019. http://dx.doi.org/10.1109/globalsip45357.2019.8969120.
Full textLiu, Guang, Shikang Wu, Yu Shi, Yuerui Zhang, Junxiong Fei, and Xia Hua. "Underwater Non-uniform Illumination Image Correction Method Based on Dark Channel and Frequency Distribution Prior." In 2021 China Automation Congress (CAC). IEEE, 2021. http://dx.doi.org/10.1109/cac53003.2021.9728308.
Full textNezhad, Hamed Yazdani, Noel P. O’Dowd, Catrin M. Davies, Ali N. Mehmanparast, and Kamran M. Nikbin. "Influence of Prior Deformation on Creep Crack Growth Behaviour of 316H Austenitic Steels." In ASME 2012 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/pvp2012-78680.
Full textZur, Richard M., Lorenzo L. Pesce, Yulei Jiang, and Charles E. Metz. "A Bayesian interpretation of the "proper" binormal ROC model using a uniform prior distribution for the area under the curve." In Medical Imaging, edited by Yulei Jiang and Berkman Sahiner. SPIE, 2007. http://dx.doi.org/10.1117/12.711689.
Full textHermanson, K. S., and K. A. Thole. "Effect of Non-Uniform Inlet Conditions on Endwall Secondary Flows." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30188.
Full textPham, Quang N., Youngjoon Suh, Bowen Shao, and Yoonjin Won. "Boiling Heat Transfer Using Spatially-Variant and Uniform Microporous Coatings." In ASME 2019 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/ipack2019-6307.
Full textHellum, Aren M., Ranjan Mukherjee, and Andrew J. Hull. "Dynamics of Pipes Conveying Fluid With a Non-Uniform Velocity Profile." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-12858.
Full textTian, Jie, Xiaopu Zhang, Yong Chen, Peter Russhard, and Hua Ouyang. "Sparse Reconstruction Method of Non-Uniform Sampling and its Application in Blade Tip Timing System." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14753.
Full textHellum, Aren M., Ranjan Mukherjee, and Andrew J. Hull. "Dynamics of Pipes Conveying Fluid With Non-Uniform Turbulent and Laminar Velocity Profiles." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30866.
Full textDiez, F. J., L. P. Bernal, and G. M. Faeth. "Self-Preserving Properties of Steady Round Nonbuoyant Turbulent Jets in Uniform Crossflows." In ASME 2004 Heat Transfer/Fluids Engineering Summer Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ht-fed2004-56110.
Full textReports on the topic "Uniform prior"
Wüthrich, Annik. L’expression de la filiation à la XXIe dynastie: reflet d’une réalité historique ou simple effet de mode? L’exemple du Livre des Morts. Verlag der Österreichischen Akademie der Wissenschaften, August 2021. http://dx.doi.org/10.1553/erc_stg_757951_a.wuethrich_l_expression_de_la_filiation_a_la_xxie_dynastie:_reflet_d_une_realit_historique_ou_simple_effet_de_mode_l_exemple_du_livre_des_morts.
Full textClausen, Jay, Susan Frankenstein, Jason Dorvee, Austin Workman, Blaine Morriss, Keran Claffey, Terrance Sobecki, et al. Spatial and temporal variance of soil and meteorological properties affecting sensor performance—Phase 2. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41780.
Full textWolfenson, David, William W. Thatcher, and James E. Kinder. Regulation of LH Secretion in the Periovulatory Period as a Strategy to Enhance Ovarian Function and Fertility in Dairy and Beef Cows. United States Department of Agriculture, December 2003. http://dx.doi.org/10.32747/2003.7586458.bard.
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