Academic literature on the topic 'Gibbs sampler'
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Journal articles on the topic "Gibbs sampler"
Ritter, Christian, and Martin A. Tanner. "Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler." Journal of the American Statistical Association 87, no. 419 (September 1992): 861–68. http://dx.doi.org/10.1080/01621459.1992.10475289.
Full textShao, Wei, Guo Qing Zhao, and Yu Jie Gai. "Mixture Normal Distribution for Gibbs Sampler and its Application in the Surface of Single Crystal." Advanced Materials Research 529 (June 2012): 585–89. http://dx.doi.org/10.4028/www.scientific.net/amr.529.585.
Full textMacEachern, Steven N., and L. Mark Berliner. "Subsampling the Gibbs Sampler." American Statistician 48, no. 3 (August 1994): 188. http://dx.doi.org/10.2307/2684714.
Full textCasella, George, and Edward I. George. "Explaining the Gibbs Sampler." American Statistician 46, no. 3 (August 1992): 167. http://dx.doi.org/10.2307/2685208.
Full textThompson, W. A., L. A. Newberg, S. Conlan, L. A. McCue, and C. E. Lawrence. "The Gibbs Centroid Sampler." Nucleic Acids Research 35, Web Server (May 8, 2007): W232—W237. http://dx.doi.org/10.1093/nar/gkm265.
Full textCasella, George, and Edward I. George. "Explaining the Gibbs Sampler." American Statistician 46, no. 3 (August 1992): 167–74. http://dx.doi.org/10.1080/00031305.1992.10475878.
Full textMaceachern, Steven N., and L. Mark Berliner. "Subsampling the Gibbs Sampler." American Statistician 48, no. 3 (August 1994): 188–90. http://dx.doi.org/10.1080/00031305.1994.10476054.
Full textZellner, Arnold, and Chung-Ki Min. "Gibbs Sampler Convergence Criteria." Journal of the American Statistical Association 90, no. 431 (September 1995): 921–27. http://dx.doi.org/10.1080/01621459.1995.10476591.
Full textUtsugi, Akio, and Toru Kumagai. "Bayesian Analysis of Mixtures of Factor Analyzers." Neural Computation 13, no. 5 (May 1, 2001): 993–1002. http://dx.doi.org/10.1162/08997660151134299.
Full textSamawi, Hani M., Martin Dunbar, and Ding-Geng (Din) Chen. "Steady-state ranked Gibbs sampler." Journal of Statistical Computation and Simulation 82, no. 8 (August 2012): 1223–38. http://dx.doi.org/10.1080/00949655.2011.575378.
Full textDissertations / Theses on the topic "Gibbs sampler"
Chimisov, Cyril. "Adapting the Gibbs sampler." Thesis, University of Warwick, 2018. http://wrap.warwick.ac.uk/108829/.
Full textPang, 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.
Full textFair, Shannon Marie. "A Bayesian Meta-Analysis Using the Gibbs Sampler." UNF Digital Commons, 1998. http://digitalcommons.unf.edu/etd/87.
Full textZhang, 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.
Full textTan, 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.
Full textAl-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.
Full textYankovskyy, 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.
Full textXu, Zhiqing. "Bayesian Inference of a Finite Population under Selection Bias." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/621.
Full textPlassmann, Florenz. "The Impact of Two-Rate Taxes on Construction in Pennsylvania." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/30622.
Full textThe 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.
Full textPh.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
Books on the topic "Gibbs sampler"
Kuo, Lynn. Bayesian computations in survival models via the Gibbs sampler. Monterey, Calif: Naval Postgraduate School, 1991.
Find full textCanty, Angelo. A system to test for convergence of the Gibbs sampler. Toronto: [s.n.], 1994.
Find full textGibbs, Alison. Bounding convergence time of the Gibbs sampler in Bayesian image restoration. Toronto: University of Toronto, Dept. of Statistics, 1998.
Find full textRosenthal, Jeffrey S. Analysis of the Gibbs sampler for a model related to James-Stein estimators. [Toronto]: University of Toronto, Dept. of Statistics, 1994.
Find full textRoberts, Gareth O. On convergence rates of Gibbs samplers for uniform distributions. [Toronto: University of Toronto, 1997.
Find full textCanty, Angelo. A system to test for convergence of Gibbs Sampler. 1995.
Find full textJun, Liu. Correlation structure and convergence rate of the Gibbs sampler. 1991.
Find full textSuess, Eric A., and Bruce E. Trumbo. Gibbs Sampling and Screening Tests: From Random Numbers to the Gibbs Sampler (Springer Texts in Statistics). Springer, 2006.
Find full textAdvances in full-information item factor analysis using the Gibbs sampler. 1993.
Find full textJandaghi, Gholamreza. Monte Carlo estimation of the distributions of the pedigree likelihood, the score statistic and the likelihood ratio statistic using the Gibbs Sampler. 1994.
Find full textBook chapters on the topic "Gibbs sampler"
Armstrong, Margaret, Alain G. Galli, Gaëlle Le Loc’h, François Geffroy, and Rémi Eschard. "Gibbs Sampler." In Plurigaussian Simulations in Geosciences, 77–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-12718-6_6.
Full textArmstrong, Margaret, Alain Galli, Hélène Beucher, Gaëlle Le Loc’h, Didier Renard, Brigitte Doligez, Rémi Eschard, and François Geffroy. "Gibbs Sampler." In Plurigaussian Simulations in Geosciences, 107–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19607-2_7.
Full textXia, Xuhua. "Gibbs sampler." In Bioinformatics and the Cell, 99–111. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90684-3_4.
Full textLiu, Jun S. "The Gibbs Sampler." In 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.
Full textRobert, Christian P., and George Casella. "The Gibbs Sampler." In 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.
Full textTanner, Martin A. "The Gibbs Sampler." In 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.
Full textRobert, Christian P., and George Casella. "The Multi-Stage Gibbs Sampler." In 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.
Full textRobert, Christian P., and George Casella. "The Two-Stage Gibbs Sampler." In 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.
Full textBarbu, Adrian, and Song-Chun Zhu. "Gibbs Sampler and Its Variants." In Monte Carlo Methods, 97–121. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-2971-5_5.
Full textKeith, Jonathan, George Sofronov, and Dirk Kroese. "The Generalized Gibbs Sampler and the Neighborhood Sampler." In 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.
Full textConference papers on the topic "Gibbs sampler"
Webb, Jon A. "Accurate halftoning using the Gibbs sampler." In EI 92, edited by James R. Sullivan, Benjamin M. Dawson, and Majid Rabbani. SPIE, 1992. http://dx.doi.org/10.1117/12.58335.
Full textSimandl, Miroslav, and Tomas Soukup. "Gibbs sampler to stochastic volatility models." In 2001 European Control Conference (ECC). IEEE, 2001. http://dx.doi.org/10.23919/ecc.2001.7076061.
Full textAi, Hua, Yang Lu, and Wenbin Guo. "Distributed Bayesian Compressive Sensing using Gibbs sampler." In 2012 International Conference on Wireless Communications & Signal Processing (WCSP 2012). IEEE, 2012. http://dx.doi.org/10.1109/wcsp.2012.6542872.
Full textLu Ling-yun, Xiao Yang, and Du Hai-feng. "Adaptive multiuser detection based on Gibbs sampler." In IET 2nd International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN 2008). IEE, 2008. http://dx.doi.org/10.1049/cp:20080982.
Full textBlunsom, Phil, Trevor Cohn, Chris Dyer, and Miles Osborne. "A Gibbs sampler for phrasal synchronous grammar induction." In 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.
Full textOrieux, F., O. Feron, and J. F. Giovannelli. "Gradient scan Gibbs sampler: An efficient high-dimensional sampler application in inverse problems." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178739.
Full textWalker, Daniel David, and Eric K. Ringger. "Model-based document clustering with a collapsed gibbs sampler." In the 14th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1401890.1401975.
Full textSari, Ilkay, Erchin Serpedin, and Bruce Suter. "Application of Gibbs Sampler for Clock Synchronization in Rbs-Protocol." In MILCOM 2006. IEEE, 2006. http://dx.doi.org/10.1109/milcom.2006.302368.
Full textKail, Georg, Jean-Yves Tourneret, Franz Hlawatsch, and Nicolas Dobigeon. "A partially collapsed Gibbs sampler for parameters with local constraints." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495806.
Full textJinghua Gu, Chen Wang, Le-Ming Shih, Tian-Li Wang, Yue Wang, R. Clarke, and Jianhua Xuan. "GIST: A Gibbs sampler to identify intracellular signal transduction pathways." In 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.
Full textReports on the topic "Gibbs sampler"
Raftery, Adrian E., and Steven Lewis. How Many Iterations in the Gibbs Sampler? Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada640705.
Full textKuo, Lynn, and Adrian F. Smith. Bayesian Computations in Survival Models via the Gibbs Sampler. Fort Belvoir, VA: Defense Technical Information Center, July 1991. http://dx.doi.org/10.21236/ada242343.
Full textWakefield, J. C., A. F. Smith, A. Racine-Poon, and A. E. Gelfand. Bayesian Analysis of Linear and Nonlinear Population Models Using the Gibbs Sampler. Fort Belvoir, VA: Defense Technical Information Center, July 1992. http://dx.doi.org/10.21236/ada254769.
Full textRaftery, Adrian E., Steven Lewis, and 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, June 1991. http://dx.doi.org/10.21236/ada241409.
Full textCheng, Hao, Rohan L. Fernando, and Dorian J. Garrick. Three Different Gibbs Samplers for BayesB Genomic Prediction. Ames (Iowa): Iowa State University, January 2014. http://dx.doi.org/10.31274/ans_air-180814-1152.
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