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Artykuły w czasopismach na temat "Gibbs sampler"
Ritter, Christian, i Martin A. Tanner. "Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler". Journal of the American Statistical Association 87, nr 419 (wrzesień 1992): 861–68. http://dx.doi.org/10.1080/01621459.1992.10475289.
Pełny tekst źródłaShao, Wei, Guo Qing Zhao i Yu Jie Gai. "Mixture Normal Distribution for Gibbs Sampler and its Application in the Surface of Single Crystal". Advanced Materials Research 529 (czerwiec 2012): 585–89. http://dx.doi.org/10.4028/www.scientific.net/amr.529.585.
Pełny tekst źródłaMacEachern, Steven N., i L. Mark Berliner. "Subsampling the Gibbs Sampler". American Statistician 48, nr 3 (sierpień 1994): 188. http://dx.doi.org/10.2307/2684714.
Pełny tekst źródłaCasella, George, i Edward I. George. "Explaining the Gibbs Sampler". American Statistician 46, nr 3 (sierpień 1992): 167. http://dx.doi.org/10.2307/2685208.
Pełny tekst źródłaThompson, W. A., L. A. Newberg, S. Conlan, L. A. McCue i C. E. Lawrence. "The Gibbs Centroid Sampler". Nucleic Acids Research 35, Web Server (8.05.2007): W232—W237. http://dx.doi.org/10.1093/nar/gkm265.
Pełny tekst źródłaCasella, George, i Edward I. George. "Explaining the Gibbs Sampler". American Statistician 46, nr 3 (sierpień 1992): 167–74. http://dx.doi.org/10.1080/00031305.1992.10475878.
Pełny tekst źródłaMaceachern, Steven N., i L. Mark Berliner. "Subsampling the Gibbs Sampler". American Statistician 48, nr 3 (sierpień 1994): 188–90. http://dx.doi.org/10.1080/00031305.1994.10476054.
Pełny tekst źródłaZellner, Arnold, i Chung-Ki Min. "Gibbs Sampler Convergence Criteria". Journal of the American Statistical Association 90, nr 431 (wrzesień 1995): 921–27. http://dx.doi.org/10.1080/01621459.1995.10476591.
Pełny tekst źródłaUtsugi, Akio, i Toru Kumagai. "Bayesian Analysis of Mixtures of Factor Analyzers". Neural Computation 13, nr 5 (1.05.2001): 993–1002. http://dx.doi.org/10.1162/08997660151134299.
Pełny tekst źródłaSamawi, Hani M., Martin Dunbar i Ding-Geng (Din) Chen. "Steady-state ranked Gibbs sampler". Journal of Statistical Computation and Simulation 82, nr 8 (sierpień 2012): 1223–38. http://dx.doi.org/10.1080/00949655.2011.575378.
Pełny tekst źródłaRozprawy doktorskie na temat "Gibbs sampler"
Chimisov, Cyril. "Adapting the Gibbs sampler". Thesis, University of Warwick, 2018. http://wrap.warwick.ac.uk/108829/.
Pełny tekst źródłaPang, Wan-Kai. "Modelling ordinal categorical data : a Gibbs sampler approach". Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323876.
Pełny tekst źródłaFair, Shannon Marie. "A Bayesian Meta-Analysis Using the Gibbs Sampler". UNF Digital Commons, 1998. http://digitalcommons.unf.edu/etd/87.
Pełny tekst źródłaZhang, Zuoshun. "Proper posterior distributions for some hierarchical models and roundoff effects in the Gibbs sampler /". Digital version accessible at:, 2000. http://wwwlib.umi.com/cr/utexas/main.
Pełny tekst źródłaTan, Aixin. "Convergence rates and regeneration of the block Gibbs sampler for Bayesian random effects models". [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024910.
Pełny tekst źródłaAl-Hamzawi, Rahim Jabbar Thaher. "Prior elicitation and variable selection for bayesian quantile regression". Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/7501.
Pełny tekst źródłaYankovskyy, Yevhen. "Application of a Gibbs Sampler to estimating parameters of a hierarchical normal model with a time trend and testing for existence of the global warming". Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/1010.
Pełny tekst źródłaXu, Zhiqing. "Bayesian Inference of a Finite Population under Selection Bias". Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/621.
Pełny tekst źródłaPlassmann, Florenz. "The Impact of Two-Rate Taxes on Construction in Pennsylvania". Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/30622.
Pełny tekst źródłaThe first part of the dissertation examines the effect of the land-building tax differential on the number of building permits that were issued in 219 municipalities in Pennsylvania between 1972 and 1994. For such count data a conventional analysis based on a continuous distribution leads to incorrect results; a discrete maximum likelihood analysis with a negative binomial distribution is more appropriate. Two models, a non-linear and a fixed effects model, are developed to examine the influence of the tax differential. Both models suggest that this influence is positive, albeit not statistically significant.
Application of maximum likelihood techniques is computationally cumbersome if the assumed distribution of the data cannot be written in closed form. The negative binomial distribution is the only discrete distribution with a variance that is larger than its mean that can easily be applied, although it might not be the best approximation of the true distribution of the data. The second part of the dissertation uses a Markov Chain Monte Carlo method to examine the influence of the tax differential on the number of building permits, under the assumption that building permits are generated by a Poisson process whose parameter varies lognormally. Contrary to the analysis in the first part, the tax is shown to have a strong and significantly positive impact on the number of permits.
The third part of the dissertation uses a fixed-effects weighted least squares method to estimate the effect of the tax differential on the value per building permit. The tax coefficient is not significantly different from zero. Still, the overall impact of the tax differential on the total value of construction is shown to be positive and statistically significant.
Ph. D.
Cao, Jun. "A Random-Linear-Extension Test Based on Classic Nonparametric Procedures". Diss., Temple University Libraries, 2009. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/48271.
Pełny tekst źródłaPh.D.
Most distribution free nonparametric methods depend on the ranks or orderings of the individual observations. This dissertation develops methods for the situation when there is only partial information about the ranks available. A random-linear-extension exact test and an empirical version of the random-linear-extension test are proposed as a new way to compare groups of data with partial orders. The basic computation procedure is to generate all possible permutations constrained by the known partial order using a randomization method similar in nature to multiple imputation. This random-linear-extension test can be simply implemented using a Gibbs Sampler to generate a random sample of complete orderings. Given a complete ordering, standard nonparametric methods, such as the Wilcoxon rank-sum test, can be applied, and the corresponding test statistics and rejection regions can be calculated. As a direct result of our new method, a single p-value is replaced by a distribution of p-values. This is related to some recent work on Fuzzy P-values, which was introduced by Geyer and Meeden in Statistical Science in 2005. A special case is to compare two groups when only two objects can be compared at a time. Three matching schemes, random matching, ordered matching and reverse matching are introduced and compared between each other. The results described in this dissertation provide some surprising insights into the statistical information in partial orderings.
Temple University--Theses
Książki na temat "Gibbs sampler"
Kuo, Lynn. Bayesian computations in survival models via the Gibbs sampler. Monterey, Calif: Naval Postgraduate School, 1991.
Znajdź pełny tekst źródłaCanty, Angelo. A system to test for convergence of the Gibbs sampler. Toronto: [s.n.], 1994.
Znajdź pełny tekst źródłaGibbs, Alison. Bounding convergence time of the Gibbs sampler in Bayesian image restoration. Toronto: University of Toronto, Dept. of Statistics, 1998.
Znajdź pełny tekst źródłaRosenthal, Jeffrey S. Analysis of the Gibbs sampler for a model related to James-Stein estimators. [Toronto]: University of Toronto, Dept. of Statistics, 1994.
Znajdź pełny tekst źródłaRoberts, Gareth O. On convergence rates of Gibbs samplers for uniform distributions. [Toronto: University of Toronto, 1997.
Znajdź pełny tekst źródłaCanty, Angelo. A system to test for convergence of Gibbs Sampler. 1995.
Znajdź pełny tekst źródłaJun, Liu. Correlation structure and convergence rate of the Gibbs sampler. 1991.
Znajdź pełny tekst źródłaSuess, Eric A., i Bruce E. Trumbo. Gibbs Sampling and Screening Tests: From Random Numbers to the Gibbs Sampler (Springer Texts in Statistics). Springer, 2006.
Znajdź pełny tekst źródłaAdvances in full-information item factor analysis using the Gibbs sampler. 1993.
Znajdź pełny tekst źródłaJandaghi, Gholamreza. Monte Carlo estimation of the distributions of the pedigree likelihood, the score statistic and the likelihood ratio statistic using the Gibbs Sampler. 1994.
Znajdź pełny tekst źródłaCzęści książek na temat "Gibbs sampler"
Armstrong, Margaret, Alain G. Galli, Gaëlle Le Loc’h, François Geffroy i Rémi Eschard. "Gibbs Sampler". W Plurigaussian Simulations in Geosciences, 77–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-12718-6_6.
Pełny tekst źródłaArmstrong, Margaret, Alain Galli, Hélène Beucher, Gaëlle Le Loc’h, Didier Renard, Brigitte Doligez, Rémi Eschard i François Geffroy. "Gibbs Sampler". W Plurigaussian Simulations in Geosciences, 107–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19607-2_7.
Pełny tekst źródłaXia, Xuhua. "Gibbs sampler". W Bioinformatics and the Cell, 99–111. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90684-3_4.
Pełny tekst źródłaLiu, Jun S. "The Gibbs Sampler". W Springer Series in Statistics, 129–51. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-0-387-76371-2_6.
Pełny tekst źródłaRobert, Christian P., i George Casella. "The Gibbs Sampler". W Springer Texts in Statistics, 285–361. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4757-3071-5_7.
Pełny tekst źródłaTanner, Martin A. "The Gibbs Sampler". W Tools for Statistical Inference, 89–107. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4684-0510-1_6.
Pełny tekst źródłaRobert, Christian P., i George Casella. "The Multi-Stage Gibbs Sampler". W Springer Texts in Statistics, 371–424. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4145-2_10.
Pełny tekst źródłaRobert, Christian P., i George Casella. "The Two-Stage Gibbs Sampler". W Springer Texts in Statistics, 337–70. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4145-2_9.
Pełny tekst źródłaBarbu, Adrian, i Song-Chun Zhu. "Gibbs Sampler and Its Variants". W Monte Carlo Methods, 97–121. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-2971-5_5.
Pełny tekst źródłaKeith, Jonathan, George Sofronov i Dirk Kroese. "The Generalized Gibbs Sampler and the Neighborhood Sampler". W Monte Carlo and Quasi-Monte Carlo Methods 2006, 537–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-74496-2_31.
Pełny tekst źródłaStreszczenia konferencji na temat "Gibbs sampler"
Webb, Jon A. "Accurate halftoning using the Gibbs sampler". W EI 92, redaktorzy James R. Sullivan, Benjamin M. Dawson i Majid Rabbani. SPIE, 1992. http://dx.doi.org/10.1117/12.58335.
Pełny tekst źródłaSimandl, Miroslav, i Tomas Soukup. "Gibbs sampler to stochastic volatility models". W 2001 European Control Conference (ECC). IEEE, 2001. http://dx.doi.org/10.23919/ecc.2001.7076061.
Pełny tekst źródłaAi, Hua, Yang Lu i Wenbin Guo. "Distributed Bayesian Compressive Sensing using Gibbs sampler". W 2012 International Conference on Wireless Communications & Signal Processing (WCSP 2012). IEEE, 2012. http://dx.doi.org/10.1109/wcsp.2012.6542872.
Pełny tekst źródłaLu Ling-yun, Xiao Yang i Du Hai-feng. "Adaptive multiuser detection based on Gibbs sampler". W IET 2nd International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN 2008). IEE, 2008. http://dx.doi.org/10.1049/cp:20080982.
Pełny tekst źródłaBlunsom, Phil, Trevor Cohn, Chris Dyer i Miles Osborne. "A Gibbs sampler for phrasal synchronous grammar induction". W the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1690219.1690256.
Pełny tekst źródłaOrieux, F., O. Feron i J. F. Giovannelli. "Gradient scan Gibbs sampler: An efficient high-dimensional sampler application in inverse problems". W ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178739.
Pełny tekst źródłaWalker, Daniel David, i Eric K. Ringger. "Model-based document clustering with a collapsed gibbs sampler". W the 14th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1401890.1401975.
Pełny tekst źródłaSari, Ilkay, Erchin Serpedin i Bruce Suter. "Application of Gibbs Sampler for Clock Synchronization in Rbs-Protocol". W MILCOM 2006. IEEE, 2006. http://dx.doi.org/10.1109/milcom.2006.302368.
Pełny tekst źródłaKail, Georg, Jean-Yves Tourneret, Franz Hlawatsch i Nicolas Dobigeon. "A partially collapsed Gibbs sampler for parameters with local constraints". W 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495806.
Pełny tekst źródłaJinghua Gu, Chen Wang, Le-Ming Shih, Tian-Li Wang, Yue Wang, R. Clarke i Jianhua Xuan. "GIST: A Gibbs sampler to identify intracellular signal transduction pathways". W 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6090677.
Pełny tekst źródłaRaporty organizacyjne na temat "Gibbs sampler"
Raftery, Adrian E., i Steven Lewis. How Many Iterations in the Gibbs Sampler? Fort Belvoir, VA: Defense Technical Information Center, wrzesień 1991. http://dx.doi.org/10.21236/ada640705.
Pełny tekst źródłaKuo, Lynn, i Adrian F. Smith. Bayesian Computations in Survival Models via the Gibbs Sampler. Fort Belvoir, VA: Defense Technical Information Center, lipiec 1991. http://dx.doi.org/10.21236/ada242343.
Pełny tekst źródłaWakefield, J. C., A. F. Smith, A. Racine-Poon i A. E. Gelfand. Bayesian Analysis of Linear and Nonlinear Population Models Using the Gibbs Sampler. Fort Belvoir, VA: Defense Technical Information Center, lipiec 1992. http://dx.doi.org/10.21236/ada254769.
Pełny tekst źródłaRaftery, Adrian E., Steven Lewis i Jeffrey D. Banfield. Three Short Papers on Sampling-Based Inference: 1. How Many Iterations in the Gibbs Sampler? 2. Model Determination. 3. Spatial Statistics. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 1991. http://dx.doi.org/10.21236/ada241409.
Pełny tekst źródłaCheng, Hao, Rohan L. Fernando i Dorian J. Garrick. Three Different Gibbs Samplers for BayesB Genomic Prediction. Ames (Iowa): Iowa State University, styczeń 2014. http://dx.doi.org/10.31274/ans_air-180814-1152.
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